CAIML welcomes ICML
CAIML welcomes the ICML conference in Vienna with the 6th Symposium on Advances in Approximate Bayesian Inference.
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July 21st 2024
- 09:00 – 19:00 CEST
- TU Wien, Campus Getreidemarkt Conference Hall TUtheSky
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1060 Vienna, Getreidemarkt 9
Building BA (Hoftrakt), 11th Floor, Room BA11B09
CAIML welcomes the ICML conference in Vienna with the 6th Symposium on Advances in Approximate Bayesian Inference.
Schedule
NOTE: This schedule is subject to change; please check again closer to the date of the symposium.
Morning Session
Chair: Christian A. Naesseth
9:00 - 10:00 Registration + Breakfast
9:30 - 11:00 Poster Session 1: All papers
11:00 - 11:15 Opening Remarks
11:15 - 11:45 Invited talk 1: Title TBD Sinead Williamson
11:45 - 12:10 Contributed talk 1: Fluctuation without dissipation: Microcanonical Langevin Monte Carlo Jakob Robnik, Uros Seljak
12:10 - 12:40 Invited talk 2: Scalable Automatic Differentiation of Probabilistic Programs Alex Lew
12:40 - 12:55 Contributed talk 2: Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities
Alberto Bordino, Stefano Favaro, Sandra Fortini
12:55 - 13:10 Contributed talk 3: In-Context In-Context Learning with Transformer Neural Processes Matthew Ashman, Cristiana Diaconu, Adrian Weller, Richard E. Turner
13:15 - 14:15 Lunch Break Self-catered: go explore Vienna together!
Afternoon Session
Chair: Siddharth Swaroop
14:15 - 15:45 Poster Session 2: All papers
15:45 - 16:15 Invited talk 3: Improvements in continuous time generative models: automated learning, nonlinear noising, and data-dependent bases Rajesh Ranganath
16:15 - 16:30 Contributed talk 4: Bayesian Optimization for Precision Agriculture with Scalable Probabilistic Models Ruhana Azam, Sang T. Truong, samuel bonfim fernandes, Andrew D.B. Leakey, Alexander Lipka, Mohammed El-Kebir, Sanmi Koyejo
16:30 - 16:45 Contributed talk 5: PAC-Bayesian Soft Actor-Critic Learning Bahareh Tasdighi, Abdullah Akgül, Manuel Haussmann, Kenny Kazimirzak Brink, Melih Kandemir
16:45 - 17:00 Contributed talk 6: Implicitly Bayesian Prediction Rules in Deep Learning Bruno Kacper Mlodozeniec, Richard E. Turner, David Krueger
17:00 - 17:30 Invited talk 4 Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics Kamélia Daudel
17:30 - 17:45 Coffee Break
17:45 - 18:45 Panel Discussion Approximate Inference for Modern AI Moderator: Tim G. J. Rudner
18:45 - 19:00 Closing Remarks
Details
You can find further details on the website of the symposium: https://approximateinference.org/