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Oral Session
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Tue 1:00
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Oral 2: Understanding Deep Learning
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Spotlight
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Wed 10:30
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Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning
Haichao Zhang · Wei Xu · Haonan Yu
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Workshop
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Designing Neural Network Collectives
Namid Stillman · Zohar Neu
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Workshop
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Fri 10:20
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Deep learning theory vs traditional theory of algorithms
Sanjeev Arora
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Workshop
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Fri 11:02
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Sifting the Signal from the Noise
Daniel Herrmann · Jacob VanDrunen
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Poster
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Mon 18:30
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Is High Variance Unavoidable in RL? A Case Study in Continuous Control
Johan Bjorck · Carla Gomes · Kilian Weinberger
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Workshop
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Fri 5:15
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Deep Learning Models for Bug Detection and Repair
Miltiadis Allamanis
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Workshop
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Gauge Equivariant Deep Q-Learning on Discrete Manifolds
Sourya Basu · Pulkit Katdare · Katherine Driggs-Campbell · Lav R Varshney
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Workshop
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Deep Learning-Based Surrogate Modelling of Thermal Plumes for Shallow Subsurface Temperature Approximation
Raphael Leiteritz · Kyle Davis · Miriam Schulte · Dirk Pflüger
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Poster
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Wed 18:30
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Benchmarking the Spectrum of Agent Capabilities
Danijar Hafner
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Oral Session
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Mon 17:00
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Oral 1: Learning in the wild, Reinforcement learning
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Poster
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Tue 10:30
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Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization
Zihan Zhou · Wei Fu · Bingliang Zhang · Yi Wu
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