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Advancing Electromyographic Continuous Speech Recognition: Signal Preprocessing and Modeling
| Advancing Electromyographic Continuous Speech Recognition: Signal Preprocessing and Modeling |
| Autore | Wand Michael |
| Pubbl/distr/stampa | KIT Scientific Publishing, 2014 |
| Descrizione fisica | 1 online resource (XVIII, 226 p. p.) |
| Soggetto non controllato |
Biosignale
Biosignals Electromyography Elektromyographie Silent Speech Interfaces Speech Recognition Spracherkennung |
| ISBN | 1000040667 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advancing Electromyographic Continuous Speech Recognition |
| Record Nr. | UNINA-9910347052403321 |
Wand Michael
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| KIT Scientific Publishing, 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (489 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks |
| ISBN | 3-031-72353-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Biosignal Processing in Medicine and Physiology. -- A deep learning multi-omics framework to combine microbiome and metabolome profiles for disease classification. -- CapsDA-Net: A Convolutional Capsule Domain Adversarial Neural Network for EEG-Based Attention Recognition. -- ComplicaCode: Enhancing Disease Complication Detection in Electronic Health Records through ICD Path Generation. -- Depression detection based on multilevel semantic features. -- Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusion. -- Identify Disease-associated MiRNA-miRNA Pairs through Deep Tensor Factorization and Semi-supervised Learning. -- Interpretable EHR Disease Prediction System Based on Disease Experts and Patient Similarity Graph (DE-PSG). -- Meteorological Data based Detection of Stroke using Machine Learning Techniques. -- OFNN-UNI: Enhanced Optimized Fuzzy Neural Networks based on Unineurons for Advanced Sepsis Classification. -- ProTeM: Unifying Protein Function Prediction via Text Matching. -- SnoreOxiNet: Non-contact Diagnosis of Nocturnal Hypoxemia Using Cross-domain Acoustic Features. -- Unveiling the Potential of Synthetic Data in Sports Science: A Comparative Study of Generative Methods. -- Medical Image Processing. -- Adaptive Fusion Boundary-Enhanced Multilayer Perceptual Network (FBAIM-Net) for Enhanced Polyp Segmentation in Medical Imaging. -- Advancing Free-breathing Cardiac Cine MRI: Retrospective Respiratory Motion Correction Via Kspace-and-Image Guided Diffusion Model. -- Blood Cell Detection and Self-attention-based Mixed Attention Mechanism. -- CellSpot: Deep Learning-Based Efficient Cell Center Detection in Microscopic Images. -- Classification of dehiscence defects in titanium and zirconium dental implants. -- CurSegNet: 3D Dental Model Segmentation Network Based on Curve Feature Aggregation. -- DBrAL: A novel uncertainty-based active learning based on deep-broad learning for medical image classi cation. -- EDPS-SST: Enhanced Dynamic Path Stitching with Structural Similarity Thresholding for Large-Scale Medical Image Stitching under Sparse Pixel Overlap. -- Hop-Gated Graph Attention Network for ASD Diagnosis via PC-Based Graph Regularization Sparse Representation. -- MISS: A Generative Pre-training and Fine-tuning Approach for Med-VQA. -- MSD-HAM-Net: A Multi-modality Fusion Network of PET/CT Images for the Prognosis of DLBCL Patients. -- Multi-Modal Multi-Scale State Space Model for Medical Visual Question Answering. -- Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. -- Point-based Weakly Supervised 2.5D Cell Segmentation. -- Relative Local Signal Strength: the Impact of Normalization on the Analysis of Neuroimaging Data with Deep Learning. -- SCANet: Dual Attention Network for Alzheimer’s Disease Diagnosis Based on Gated Residual and Spatial Asymmetry Mechanisms. -- SCST: Spatial Consistent Swin Transformer for Multi-Focus Biomedical Microscopic Image Fusion. -- KnowMIM: a self-supervised pre-training framework based on knowledge-guided masked image modeling for retinal vessel segmentation. -- Transferability of Non-Contrastive Self-Supervised Learning to Chronic Wound Image Recognition. -- Two-stage Medical Image-text Transfer with Supervised Contrastive Learning. |
| Record Nr. | UNINA-9910887886003321 |
|
Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VII / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VII / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (476 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks |
| ISBN | 3-031-72350-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Speech Processing. -- Breaking the Corpus Bottleneck for Multi-dialect Speech Recognition with Flexible Adapters. -- Developmental Predictive Coding Model for Early Infancy Mono- and Bilingual Vocal Continual Learning. -- T-DVAE: A Transformer-based Dynamical Variational Autoencoder for Speech. -- Natural Language Processing. -- A Generalizable Context-Aware Deep Learning Model for Abusive Language Detection. -- A Novel Graph Neural Network Based Model for Text Classification. -- ABSA Methodology Based on Interval-enhanced Talking-heads Attention Network. -- An Evaluation Dataset for Targeted Sentiment Analysis in Long-Form Chinese News Articles. -- Anti-Hate Speech Framework: Leveraging Hedging Hyperbolic Learning. -- Combining Data Generation and Active Learning for Low-Resource Question Answering. -- CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-Thought. -- EKD: Effective Knowledge Distillation for Few-Shot Sentiment Analysis. -- End-to-End Training of Back-Translation Framework with Categorical Reparameterization Trick. -- Enhancing Zero-Shot Translation in Multilingual Neural Machine Translation: Focusing on obtaining Location-Agnostic Representations. -- Generative Sentiment Analysis via Latent Category Distribution and Constrained Decoding. -- Improve Shallow Decoder Based Transformer with Structured Expert Prediction. -- KELTP: Keyword-Enhanced Learned Token Pruning for Knowledge-Grounded Dialogue. -- Knowledge Base Question Generation via Data Augmentation with Dynamic-prompt. -- Lifelong Sentiment Classification Based on Adaptive Parameter Updating. -- Multi-stage vs Single-stage: A Local Information Focused Approach for Overlapping Event Extraction. -- PLIClass: Weakly Supervised Text Classification with Iterative Training and Denoisy Inference. -- Reinforced Keyphrase Genertion with Multi-Dimensional Reward. -- Reinforced Multi-Teacher Knowledge Distillation for Unsupervised Sentence Representation. -- Summarizing Like Human: Edit-Based Text Summarization with Keywords. -- Towards Persona-oriented LLM-generated Text Detection: Benchmark Dataset and Method. -- Use of Riemannian distance metric to verify topological similarity of acoustic and text domains. -- WKE: Word-level Knowledge Enrichment for Aspect Term Extraction. -- Language Modeling. -- A general-purpose material entity extraction method from large compound corpora using fine tuning of character features. -- Efficient Fine-tuning for Low-resource Tibetan Pre-trained Language Models. -- Enhancing LM’s Task Adaptability: Powerful Post-Training Framework with Reinforcement Learning from Model Feedback. -- GL-NER: Generation-aware Large Language Models for Few-shot Named Entity Recognition. |
| Record Nr. | UNINA-9910887892803321 |
|
Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IV / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IV / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (449 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks |
| ISBN | 3-031-72341-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Brain-inspired ComputingBrain-inspired Computing. -- A Multiscale Resonant Spiking Neural Network for Music Classification. -- Masked Image Modeling as a Framework for Self-Supervised Learning across Eye Movements. -- Serial Order Codes for Dimensionality Reduction in the Learning of Higher-Order Rules and Compositionality in Planning. -- Sparsity aware Learning in Feedback-driven Differential Recurrent Neural Networks. -- Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion. -- Cognitive and Computational Neuroscience. -- Analysis of a Generative Model of Episodic Memory Based on Hierarchical VQ-VAE and Transformer. -- Biologically-plausible Markov Chain Monte Carlo Sampling from Vector Symbolic Algebra-encoded Distributions. -- Dynamic Graph for Biological Memory Modeling: A System-Level Validation. -- EEG features learned by convolutional neural networks reflect alterations of social stimuli processing in autism. -- Estimate of the Storage Capacity of q-Correlated Patterns in Hopfield Neural Networks. -- An Accuracy-Shaping Mechanism for Competitive Distributed Learning. -- Explainable Artificial Intelligence. -- Counterfactual Contrastive Learning for Fine Grained Image Classification. -- Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space. -- Exploring Task-Specific Dimensions in Word Embeddings Through Automatic Rule Learning. -- Generally-Occurring Model Change for Robust Counterfactual Explanations. -- Model Based Clustering of Time Series Utilizing Expert ODEs. -- Towards Generalizable and Interpretable AI-Modified Image Detectors. -- Understanding Deep Networks via Multiscale Perturbations. -- Robotics. -- Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning. -- Neural Formation A*: A Knowledge-Data Hybrid-Driven Path Planning Algorithm for Multi-agent Formation Cooperation. -- Robust Navigation for Unmanned Surface Vehicle Utilizing Improved Distributional Soft Actor-Critic. -- When Robots Get Chatty: Grounding Multimodal Human-Robot Conversation and Collaboration. -- Reinforcement Learning. -- Asymmetric Actor-Critic for Adapting to Changing Environments in Reinforcement Learning. -- Building surrogate models using trajectories of agents trained by Reinforcement Learning. -- Demand-Responsive Transport Dynamic Scheduling Optimization Based on Multi-Agent Reinforcement Learning under Mixed Demand. -- Dual Action Policy for Robust Sim-to-Real Reinforcement Learning. -- Enhancing Visual Generalization in Reinforcement Learning with Cycling Augmentation. -- Speeding up Meta-Exploration via Latent Representation. |
| Record Nr. | UNINA-9910887878503321 |
|
Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part II / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part II / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72335-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Computer Vision: Classification. -- A WEAKLY SUPERVISED PART DETECTION METHOD FOR ROBUST FINE-GRAINED CLASSIFICATION. -- An Energy Sampling Replay-Based Continual Learning Framework. -- Coarse-to-Fine Granularity in MultiScale FeatureFusion Network for SAR Ship Classification. .-Multi-scale convolutional attention fuzzy broad network for few-shot hyperspectral image classification. -- Self Adaptive Threshold Pseudo-labeling and Unreliable Sample Contrastive Loss for Semi-supervised Image Classification. -- Computer Vision: Object Detection. -- CIA-Net:Cross-modal Interaction and Depth Quality-Aware Network for RGB-D Salient Object Detection. -- CPH DETR: Comprehensive Regression Loss for End-to-End Object Detection. -- DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion. -- EMDFNet: Efficient Multi-scale and Diverse Feature Network for Traffic Sign Detection. -- Global-Guided Weighted Enhancement for Salient Object Detection. -- KDNet: Leveraging Vision-Language Knowledge Distillation for Few-Shot Object Detection. -- MUFASA: Multi-View Fusion and Adaptation Network with Spatial Awareness for Radar Object Detection. -- One-Shot Object Detection with 4D-Correlation and 4D-Attention. -- Small Object Detection Based on Bidirectional Feature Fusion and Multi-scale Distillation. .-SRA-YOLO: Spatial Resolution Adaptive YOLO for Semi-Supervised Cross-Domain Aerial Object Detection. -- Computer Vision: Security and Adversarial Attacks. -- BiFAT: Bilateral Filtering and Attention Mechanisms in a Two-Stream Model for Deepfake Detection. -- EL-FDL: Improving Image Forgery Detection and Localization via Ensemble Learning. -- Generalizable Deepfake Detection with Unbiased Feature Extraction and Low-level Forgery Enhancement. -- Generative Universal Nullifying Perturbation for Countering Deepfakes through Combined Unsupervised Feature Aggregation. -- Noise-NeRF: Hide Information in Neural Radiance Field using Trainable Noise. -- Unconventional Face Adversarial Attack. Computer Vision: Image EnhancementComputer Vision: Image Enhancement. -- Computer Vision: Image Enhancement. -- A Study in Dataset Pruning for Image Super-Resolution. -- EDAFormer:Enhancing Low-Light Images with a Dual-Attention Transformer. -- Image Matting Based on Deep Equilibrium Models. -- Computer Vision: 3D Methods. -- ControlNeRF: Text-Driven 3D Scene Stylization via Diffusion Model. -- Interactive Color Manipulation in NeRF: A Point Cloud and Palette-driven Approach. -- Multimodal Monocular Dense Depth Estimation with Event-Frame Fusion using Transformer. -- SAM-NeRF: NeRF-based 3D Instance Segmentation with Segment Anything Model. -- Towards High-Accuracy Point Cloud Registration with Channel Self-Attention and Angle Invariance. |
| Record Nr. | UNINA-9910887885503321 |
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Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VI / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VI / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (353 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72347-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Multimodality. -- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework. -- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction. -- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking. -- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva. -- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation. -- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval. -- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling. -- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment. -- Federated Learning. -- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks. -- An Accuracy-Shaping Mechanism for Competitive Distributed Learning. -- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection. -- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition. -- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training. -- Security Assessment of Hierarchical Federated Deep Learning. -- Time Series Processing. -- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting. -- Fusion of image representations for time series classification with deep learning. -- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting. -- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time Series Analysis. -- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting. -- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection. -- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning. |
| Record Nr. | UNINA-9910887891103321 |
|
Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part X / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part X / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (469 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72359-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Workshop: AI in Drug Discovery. -- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration. -- De novo Drug Design – Do We Really Want To Be “Original”? -- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting. -- Neural SHAKE: Geometric Constraints in Graph Generative Models. -- Scaffold Splits Overestimate Virtual Screening Performance. -- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS. -- Workshop: Reservoir Computing. -- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability. -- Non-dissipative Reservoir Computing approaches for time-series classification. -- Onion Echo State Networks A Preliminary Analysis of Dynamics. -- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series. -- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs. -- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware Implementation. -- Restricted Reservoirs on Heterogeneous Timescales. -- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks. -- Clean-image Backdoor Attacks. -- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension. -- Robustness of biologically grounded neural networks against image perturbations. -- Some Comparisons of Linear and Deep ReLU Network Approximation. -- Unlearnable Examples Detection via Iterative Filtering. -- Special Session: Neurorobotics. -- Action recognition system integrating motion and object detection. -- Active Vision for Physical Robots using the Free Energy Principle. -- Learning Low-Level Causal Relations using a Simulated Robotic Arm. -- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks. -- Robotic Model of the Mirror Neuron System: a Revival. -- Self-organized attractoring in locomoting animals and robots: an emerging field. -- Special Session: Spiking Neural Networks. -- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme. -- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network. -- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training. -- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices. -- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion. -- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking Neural Networks. -- Temporal Contrastive Learning for Spiking Neural Networks. |
| Record Nr. | UNINA-9910887893203321 |
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Wand Michael
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part I / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part I / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (497 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72332-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Theory of Neural Networks and Machine Learning. -- Multi-label Robust Feature Selection via Subspace-Sparsity Learning. -- Nullspace-based metric for classification of dynamical systems and sensors. -- On the Bayesian Interpretation of Robust Regression Neural Networks. -- Probability-Generating Function Kernels for Spherical Data. -- Tailored Finite Point Operator Networks for Interface problems. -- Novel Methods in Machine Learning. -- A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra class. -- Adaptive Compression of the Latent Space in Variational Autoencoders. -- Asymmetric Isomap for Dimensionality Reduction and Data Visualization. -- CALICO: Confident Active Learning with Integrated Calibration. -- Improved Multi-hop Reasoning through Sampling and Aggregating. -- Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks. -- Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. -- Safe Data Resampling Method based on Counterfactuals Analysis. -- Test-Time Augmentation for Traveling Salesperson Problem. -- Novel Neural Architectures. -- Resonator-Gated RNNs. -- Towards a model of associative memory with learned distributed representations. -- Neural Architecture Search. -- Accelerated NAS via pretrained ensembles and multi-fidelity Bayesian Optimization. -- Feature Activation-Driven Zero-Shot NAS: A Contrastive Learning Framework. -- NAS-Bench-Compre: A Comprehensive Neural Architecture Search Benchmark with Customizable Components. -- NAVIGATOR-D3: Neural Architecture search using VarIational Graph Auto-encoder Toward Optimal aRchitecture Design for Diverse Datasets. -- ResBuilder: Automated Learning of Depth with Residual Structures -- Self-Organization. -- A Neuron Coverage-based Self-Organizing Approach for RBFNNs in Multi-Class Classification Tasks. -- Self-Organising Neural Discrete Representation Learning à la Kohonen. -- Neural Processes. -- Combined Global and Local Information Diffusion of Neural Processes. -- Topology of Neural Processes. -- Novel Architectures for Computer Vision. -- DEEPAM: Toward Deeper Attention Module in Residual Convolutional Neural Networks. -- Differentiable Largest Connected Component Layer for Image Mattin. -- Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features. -- Transformer Tracker based on Multi-level Residual Perception Structure. .-Multimodal Architectures. -- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking. -- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation. -- Fairness in Machine Learning. -- CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-off in Machine Learning. |
| Record Nr. | UNINA-9910887879403321 |
|
Wand Michael
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (509 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72356-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Human-Computer Interfaces. -- Combining Contrastive Learning and Sequence Learning for Automated Essay Scoring. -- PIDM: Personality-aware Interaction Diffusion Model for gesture generation. -- Prompt Design using Past Dialogue Summarization for LLMs to Generate the Current Appropriate Dialogue. -- Recommender Systems. -- Click-Through Rate Prediction Based on Filtering-enhanced with Multi-Head Attention. -- Enhancing Sequential Recommendation via Aligning Interest Distributions. -- LGCRS: LLM-Guided Representation-Enhancing for Conversational Recommender System. -- Multi-intent Aware Contrastive Learning for Sequential Recommendation. -- Subgraph Collaborative Graph Contrastive Learning for Recommendation. -- Time-Aware Squeeze-Excitation Transformer for Sequential Recommendation. -- Environment and Climate. -- Carbon Price Forecasting with LLM-based Refinement and Transfer-Learning. -- Challenges, Methods, Data – a Survey of Machine Learning in Water Distribution Networks. -- Day-ahead scenario analysis of wind power based on ICGAN and IDTW-Kmedoids. -- Enhancing Weather Predictions: Super-Resolution via Deep Diffusion Models. -- Hybrid CNN-MLP for Wastewater Quality Estimation. -- Short-term Forecasting of Wind Power Using CEEMDAN-ICOA-GRU Model. -- City Planning. -- Predicting City Origin-Destination Flow with Generative Pre-training. -- Vehicle-based Evolutionary Travel Time Estimation with Deep Meta Learning. -- Machine Learning in Engineering and Industry. -- APF-DQN: Adaptive Objective Pathfinding via Improved Deep Reinforcement Learning among Building Fire Hazard. -- DDPM-MoCo: Enhancing the Generation and Detection of Industrial Surface Defects through Generative and Contrastive Learning. -- Detecting Railway Track Irregularities Using Conformal Prediction. -- Identifying the Trends of Technological Convergence between Domains using a Heterogeneous Graph Perspective: A Case Study of the Graphene Industry. -- Machine Learning Accelerated Prediction of 3D Granular Flows in Hoppers. -- RD-Crack: A Study of Concrete Crack Detection Guided by a Residual Neural Network Improved Based on Diffusion Modeling. -- Applications in Finance. -- Anomaly Detection in Blockchain Using Multi-source Embedding and Attention Mechanism. -- Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems. -- MSIF: Multi-Source Information Fusion for Financial Question Answering. -- Artificial Intelligence in Education. -- A Temporal-Enhanced Model for Knowledge Tracing. -- Social Network Analysis. -- Position and type aware anchor link prediction across social networks. -- Artificial Intelligence and Music. -- LSTM-MorA: Melody-Accompaniment Classification of MIDI Tracks. -- Software Security. -- Ch4os: Discretized Generative Adversarial Network for Functionality-preserving Evasive Modification on Malware. -- SSA-GAT: Graph-based Self-supervised Learning for Network Intrusion Detection. |
| Record Nr. | UNINA-9910887873603321 |
|
Wand Michael
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part V / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko
| Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part V / / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Autore | Wand Michael |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (462 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MalinovskáKristína
SchmidhuberJürgen TetkoIgor V |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Computers Application software Computer networks Artificial Intelligence Computing Milieux Computer and Information Systems Applications Computer Communication Networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-72344-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Graph Neural Networks. -- 3D Lattice Deformation Prediction with Hierarchical Graph Attention Networks. -- Beyond Homophily: Attributed Graph Anomaly Detection via Heterophily-aware Contrastive Learning Network. -- Boosting Attributed Graph Anomaly Detection via Negative Sample Awareness. -- CauchyGCN: Preserving Local Smoothness in Graph Convolutional Networks via a Cauchy-Based Message-Passing Scheme and Clustering Analysis. -- ComMGAE: Community Aware Masked Graph AutoEncoder. -- CTQW-GraphSAGE: Trainabel Continuous-Time Quantum Walk On Graph. -- Edged Weisfeiler-Lehman algorithm. -- Enhancing Fraud Detection via GNNs with Synthetic Fraud Node Generation and Integrated Structural Features. -- Graph-Guided Multi-View Text Classification: Advanced Solutions for Fast Inference. -- Invariant Graph Contrastive Learning for Mitigating Neighborhood Bias in Graph Neural Network based Recommender Systems. -- Key Substructure-Driven Backdoor Attacks on Graph Neural Networks. -- Missing Data Imputation via Neighbor Data Feature-enriched Neural Ordinary Differential Equations. -- Multi-graph Fusion and Virtual Node Enhanced Graph Neural Networks. -- STGNA: Spatial-Temporal Graph Convolutional Networks with Node Level Attention for Shortwave Communications Parameters Forecasting. -- Virtual Nodes based Heterogeneous Graph Convolutional Neural Network for Efficient Long-Range Information Aggregation. -- Large Language Models. -- A Three-Phases-LORA Finetuned Hybrid LLM Integrated with Strong Prior Module in the Eduation Context. -- An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration. -- Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models. -- BiosERC: Integrating Biography Speakers Supported by LLMs for ERC Tasks. -- CSAFT: Continuous Semantic Augmentation Fine-Tuning for Legal Large Language Models. -- FashionGPT: A Large Vision-Language Model for Enhancing Fashion Understanding. -- Generative Chain-of-Thought for Zero-shot Cognitive Reasoning. -- Generic Joke Generation with Moral Constraints. -- Large Language Model Ranker with Graph Reasoning for Zero-Shot Recommendation. -- REM: A Ranking-based Automatic Evaluation Method for LLMs. -- Semantics-Preserved Distortion for Personal Privacy Protection in Information Management. -- Towards Minimal Edits in Automated Program Repair: A Hybrid Framework Integrating Graph Neural Networks and Large Language Models. -- Unveiling Vulnerabilities in Large Vision-Language Models: The SAVJ Jailbreak Approach. |
| Record Nr. | UNINA-9910887875703321 |
|
Wand Michael
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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