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Tutorial
Mon 9:35 Physics-Informed Inductive Biases in Deep Learning
Miles Cranmer · Shirley Ho
Tutorial
Mon 10:50 Accelerating Simulations in Physics with Deep Learning
Miles Cranmer · Shirley Ho
Tutorial
Mon 12:05 The Problem with Deep Learning for Physics (and how to fix it)
Miles Cranmer · Shirley Ho
Oral
Tue 0:00 E(n) Equivariant Normalizing Flows
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling
Oral
Tue 0:00 Framing RNN as a kernel method: A neural ODE approach
Adeline Fermanian · Pierre Marion · Jean-Philippe Vert · Gérard Biau
Oral
Tue 0:00 Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics
Carles Domingo i Enrich · Youssef Mroueh
Oral
Tue 0:20 A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck · Mark Sellke
Oral
Tue 0:20 Learning to Draw: Emergent Communication through Sketching
Daniela Mihai · Jonathon Hare
Oral
Tue 0:40 Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons
Paul Haider · Benjamin Ellenberger · Laura Kriener · Jakob Jordan · Walter Senn · Mihai A. Petrovici
Oral
Tue 1:00 Attention over Learned Object Embeddings Enables Complex Visual Reasoning
David Ding · Felix Hill · Adam Santoro · Malcolm Reynolds · Matt Botvinick
Oral
Tue 1:20 Learning Frequency Domain Approximation for Binary Neural Networks
Yixing Xu · Kai Han · Chang Xu · Yehui Tang · Chunjing XU · Yunhe Wang
Poster
Tue 8:30 SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness
Jongheon Jeong · Sejun Park · Minkyu Kim · Heung-Chang Lee · Do-Guk Kim · Jinwoo Shin