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Workshop
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Fri 6:30
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Intro: Reasoning with Deep Learning Architectures Based on System 2 Inductive Biases
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Workshop
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Fri 14:02
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Invited Talk: A deep learning theory for neural networks grounded in physics
Benjamin Scellier
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Workshop
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On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Marc Vischer · Henning Sprekeler · Robert Lange
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Poster
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Thu 9:00
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Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake Snell · Richard Zemel
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Poster
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Thu 17:00
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Adapting to Reward Progressivity via Spectral Reinforcement Learning
Michael Dann · John Thangarajah
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Poster
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Mon 9:00
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A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
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Poster
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Thu 9:00
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Deconstructing the Regularization of BatchNorm
Yann Dauphin · Ekin Cubuk
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Poster
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Thu 17:00
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DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
Minjia Zhang · Menghao Li · Chi Wang · Mingqin Li
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Poster
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Tue 1:00
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Activation-level uncertainty in deep neural networks
Pablo Morales-Alvarez · Daniel Hernández-Lobato · Rafael Molina · José Miguel Hernández Lobato
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Workshop
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Fri 11:00
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Keynote 6: Liangwei Ge. Title: Deep learning challenges and how Intel is addressing them
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Workshop
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Fri 5:15
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Geometric Deep Learning
Fernando Gama
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Poster
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Thu 17:00
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Neural Thompson Sampling
Weitong ZHANG · Dongruo Zhou · Lihong Li · Quanquan Gu
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