아래와 같이 초청특강을 개최하오니 많은 참석 바랍니다.

 

1. 일시 : 2026년 7월 7일(화), 오후 3시~

 

2. 장소 : 통계학과 스마트강의실 (자연대연구실험동 222호)

 

3. 연사 : 송성호 교수 (Division of Statistics and Data Science, Univ. of Cincinnati)

 

4. 연제 : Introduction to Bayesian Deep Learning

 

Abstract

 

Deep learning has demonstrated remarkable success in a wide range of applications, yet its ability to quantify uncertainty remains limited. Bayesian deep learning combines the predictive power of deep neural networks with the probabilistic framework of Bayesian inference, enabling more reliable predictions and principled uncertainty quantification. This presentation provides a brief introduction to the fundamental concepts of Bayesian deep learning, including Bayesian neural networks, approximate inference methods, and modern approaches for uncertainty estimation. The talk highlights how Bayesian methods can enhance the robustness, interpretability, and trustworthiness of deep learning models in scientific and real-world applications.