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08/17/2023
Half-Hop: A graph upsampling approach for slowing down message passing
Message passing neural networks have shown a lot of success on graph-str...
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05/01/2023
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
Representation learning and exploration are among the key challenges for...
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03/15/2023
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
Natural behavior consists of dynamics that are complex and unpredictable...
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12/06/2022
Understanding Self-Predictive Learning for Reinforcement Learning
We study the learning dynamics of self-predictive learning for reinforce...
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06/16/2022
BYOL-Explore: Exploration by Bootstrapped Prediction
We present BYOL-Explore, a conceptually simple yet general approach for ...
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06/14/2022
Learning Behavior Representations Through Multi-Timescale Bootstrapping
Natural behavior consists of dynamics that are both unpredictable, can s...
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12/12/2021
Quantifying and Understanding Adversarial Examples in Discrete Input Spaces
Modern classification algorithms are susceptible to adversarial examples...
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07/20/2021
Large-scale graph representation learning with very deep GNNs and self-supervision
Effectively and efficiently deploying graph neural networks (GNNs) at sc...
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02/12/2021
Bootstrapped Representation Learning on Graphs
Current state-of-the-art self-supervised learning methods for graph neur...
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01/06/2021
Geometric Entropic Exploration
Exploration is essential for solving complex Reinforcement Learning (RL)...
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11/18/2020
