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07/12/2022
Wayformer: Motion Forecasting via Simple Efficient Attention Networks
Motion forecasting for autonomous driving is a challenging task because ...
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09/27/2021
Training on Test Data with Bayesian Adaptation for Covariate Shift
When faced with distribution shift at test time, deep neural networks of...
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07/15/2021
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Exploration in reinforcement learning is a challenging problem: in the w...
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11/05/2020
Amortized Conditional Normalized Maximum Likelihood
While deep neural networks provide good performance for a range of chall...
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06/08/2020
Conservative Q-Learning for Offline Reinforcement Learning
Effectively leveraging large, previously collected datasets in reinforce...
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03/19/2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
Deep reinforcement learning algorithms require large amounts of experien...
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12/26/2018
Learning to Walk via Deep Reinforcement Learning
Deep reinforcement learning suggests the promise of fully automated lear...
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12/13/2018
Soft Actor-Critic Algorithms and Applications
Model-free deep reinforcement learning (RL) algorithms have been success...
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03/19/2018
Composable Deep Reinforcement Learning for Robotic Manipulation
Model-free deep reinforcement learning has been shown to exhibit good pe...
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01/04/2018
