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Mon 2:30 On Incorporating Inductive Biases into VAEs
Ning Miao · Emile Mathieu · Siddharth N · Yee Whye Teh · Tom Rainforth
Mon 2:30 The Role of Pretrained Representations for the OOD Generalization of RL Agents
Frederik Träuble · Andrea Dittadi · Manuel Wuthrich · Felix Widmaier · Peter Gehler · Ole Winther · Francesco Locatello · Olivier Bachem · Bernhard Schoelkopf · Stefan Bauer
Mon 2:30 Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms
Simin Hong · Anthony Cohn · David Hogg
Mon 2:30 PF-GNN: Differentiable particle filtering based approximation of universal graph representations
Mohammed Haroon Dupty · Yanfei Dong · Wee Sun Lee
Mon 2:30 Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing
Iro Laina · Yuki Asano · Andrea Vedaldi
Mon 2:30 Stability Regularization for Discrete Representation Learning
Adeel Pervez · Efstratios Gavves
Mon 10:30 Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin · Yaqi Duan · Mengdi Wang · Yu-Xiang Wang
Mon 10:30 Continuous-Time Meta-Learning with Forward Mode Differentiation
Tristan Deleu · David Kanaa · Leo Feng · Giancarlo Kerg · Yoshua Bengio · Guillaume Lajoie · Pierre-Luc Bacon
Mon 10:30 Environment Predictive Coding for Visual Navigation
Santhosh Kumar Ramakrishnan · Tushar Nagarajan · Ziad Al-Halah · Kristen Grauman
Mon 10:30 NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
Mikhail Galkin · Etienne Denis · Jiapeng Wu · William Hamilton
Mon 10:30 Illiterate DALL-E Learns to Compose
Gautam Singh · Fei Deng · Sungjin Ahn
Mon 10:30 Auto-Transfer: Learning to Route Transferable Representations
Keerthiram Murugesan · Vijay Sadashivaiah · Ronny Luss · Karthikeyan Shanmugam · Pin-Yu Chen · Amit Dhurandhar