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Workshop
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Fri 8:00
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Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment
Yuu Jinnai · Tetsuro Morimura · Kaito Ariu · Kenshi Abe
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Workshop
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Collective Variable Free Transition Path Sampling with Generative Flow Network
Kiyoung Seong · Seonghyun Park · SEONGHWAN KIM · Woo Youn Kim · Sungsoo Ahn
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Workshop
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Distributional Monte-Carlo Planning with Thompson Sampling in Stochastic Environments
DAM Tuan · Brahim Driss · Odalric-Ambrym Maillard
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Workshop
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Revisiting Score Function Estimators for k-Subset Sampling
Klas Wijk · Ricardo Vinuesa · Hossein Azizpour
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Workshop
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Sat 1:10
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Contributed: Adaptive Sampling for Continuous Group Equivariant Neural Networks
Berfin Inal
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Poster
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Tue 2:30
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Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
Youwei Shu · Xi Xiao · Derui Wang · Yuxin Cao · Siji Chen · Minhui Xue · Linyi Li · Bo Li
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Workshop
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Discrete Diffusion Posterior Sampling for Protein Design
Mert Cemri · Ajil Jalal · Kannan Ramchandran
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Poster
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Wed 4:30
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Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation
Kartik Sharma · Srijan Kumar · Rakshit Trivedi
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Poster
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Thu 4:30
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Sample as you Infer: Predictive Coding with Langevin Dynamics
Umais Zahid · Qinghai Guo · Zafeirios Fountas
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Poster
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Thu 4:30
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A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples
Ben Adcock · Juan Cardenas · Nick Dexter
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Poster
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Thu 4:30
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Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory
Kai Xu · Hong Ge
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Poster
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Tue 2:30
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Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
Yingru Li · Jiawei Xu · Lei Han · Zhi-Quan Luo
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