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Poster
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Tue 21:00 |
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces Zaheen Ahmad · Levi Lelis · Michael Bowling |
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Spotlight
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Tue 7:00 |
Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates Wenhao Luo · Wen Sun · Ashish Kapoor |
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Spotlight
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Thu 19:10 |
Sinkhorn Natural Gradient for Generative Models Zebang Shen · Zhenfu Wang · Alejandro Ribeiro · Hamed Hassani |
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Workshop
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Fri 10:30 |
Session 2 | Invited talk: Phiala Shanahan, "Generative Flow Models for Gauge Field Theory" Phiala Shanahan · Atilim Gunes Baydin |
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Poster
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Tue 9:00 |
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification Francesca Mignacco · Florent Krzakala · Pierfrancesco Urbani · Lenka Zdeborová |
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Workshop
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Sat 4:45 |
I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning Jessica Forde · Francisco Ruiz · Melanie Fernandez Pradier · Aaron Schein · Finale Doshi-Velez · Isabel Valera · David Blei · Hanna Wallach |
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Poster
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Thu 9:00 |
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE Ding Zhou · Xue-Xin Wei |
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Poster
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Tue 9:00 |
On the Theory of Transfer Learning: The Importance of Task Diversity Nilesh Tripuraneni · Michael Jordan · Chi Jin |
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Poster
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Thu 9:00 |
Learning Latent Space Energy-Based Prior Model Bo Pang · Tian Han · Erik Nijkamp · Song-Chun Zhu · Ying Nian Wu |
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Poster
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Tue 9:00 |
Cross-validation Confidence Intervals for Test Error Pierre Bayle · Alexandre Bayle · Lucas Janson · Lester Mackey |
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Oral
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Tue 18:30 |
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory Yufeng Zhang · Qi Cai · Zhuoran Yang · Yongxin Chen · Zhaoran Wang |
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Poster
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Tue 21:00 |
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach · XINYANG GENG · Sergey Levine · Russ Salakhutdinov |