LEADER 01827nam 2200361 450 001 9910633959803321 005 20230325140322.0 010 $a1-80356-045-2 035 $a(CKB)5700000000338764 035 $a(NjHacI)995700000000338764 035 $a(EXLCZ)995700000000338764 100 $a20230325d2022 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aBayesian Inference $eRecent Advantages /$fedited by Niansheng Tang 210 1$aLondon :$cIntechOpen,$d2022. 215 $a1 online resource (126 pages) 311 $a1-80356-044-4 330 $aWith growing interest in data mining and its merits, including the incorporation of historical or experiential information into statistical analysis, Bayesian inference has become an important tool for analyzing complicated data and solving inverse problems in various fields such as artificial intelligence. This book introduces recent developments in Bayesian inference, and covers a variety of topics including robust Bayesian estimation, solving inverse problems via Bayesian theories, hierarchical Bayesian inference, and its applications for scattering experiments. We hope that this book will stimulate more extensive research on Bayesian fronts to include theories, methods, computational algorithms and applications in various fields such as data science, AI, machine learning, and causality analysis. 517 $aBayesian Inference 606 $aBayesian statistical decision theory 615 0$aBayesian statistical decision theory. 676 $a519.542 702 $aTang$b Niansheng 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910633959803321 996 $aBayesian inference$9671625 997 $aUNINA