My experience of Bayesian Inference and Deep Learning
Date: 26 February 2021, Friday
Time: 4pm AEDT
Speaker: A/Prof. Richard Xu (University of Technology Sydney)
Abstract:
In a research environment where deep learning methods dominate, Bayesian framework still plays a vital role. In this talk, I will first illustrate Bayesian inference through a small tutorial. Then I will describe some of the latest research results (including some of my own works), in which Bayesian inference has been used to explain and assist (and assisted by) deep learning. Finally, I will give some thoughts on the future of Bayesian inference.
Bio:
Richard Yi Da Xu is an Associate Professor at the University of Technology, Sydney (UTS). He leads a team of 25 people, includes postdoc, PhD students, and data engineers; His primary research is in machine learning and artificial intelligence. Richard published at many top international conferences, including AAAI, IJCAI, ECAI, ECCV, AI-STATS and ICDM as well as many top IEEE Transactions: IEEE-(TNNLS, TIP, TSP, TKDE, MC and T-Cybernetics). Since 2009, he created 2000+ slides of free machine learning online PhD training material as well as many online ML videos. His team has collaborated with many Australian industries in finance, e-commerce, government, transport, utilities, defence, agricultural, communication and legal sectors. He established a Deep Learning Sydney meetup which has 4400+ members, one of the largest of its kind in Australia. He was representing Australia to attend ISO JTC1 SC42 (Artificial Intelligence)’s first plenary.
Link: https://au.bbcollab.com/guest/fcf219c74ac743e89565a9e6e8d349a9
Date: 26 February 2021, Friday
Time: 4pm AEDT
Speaker: A/Prof. Richard Xu (University of Technology Sydney)
Abstract:
In a research environment where deep learning methods dominate, Bayesian framework still plays a vital role. In this talk, I will first illustrate Bayesian inference through a small tutorial. Then I will describe some of the latest research results (including some of my own works), in which Bayesian inference has been used to explain and assist (and assisted by) deep learning. Finally, I will give some thoughts on the future of Bayesian inference.
Bio:
Richard Yi Da Xu is an Associate Professor at the University of Technology, Sydney (UTS). He leads a team of 25 people, includes postdoc, PhD students, and data engineers; His primary research is in machine learning and artificial intelligence. Richard published at many top international conferences, including AAAI, IJCAI, ECAI, ECCV, AI-STATS and ICDM as well as many top IEEE Transactions: IEEE-(TNNLS, TIP, TSP, TKDE, MC and T-Cybernetics). Since 2009, he created 2000+ slides of free machine learning online PhD training material as well as many online ML videos. His team has collaborated with many Australian industries in finance, e-commerce, government, transport, utilities, defence, agricultural, communication and legal sectors. He established a Deep Learning Sydney meetup which has 4400+ members, one of the largest of its kind in Australia. He was representing Australia to attend ISO JTC1 SC42 (Artificial Intelligence)’s first plenary.
Link: https://au.bbcollab.com/guest/fcf219c74ac743e89565a9e6e8d349a9
