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06/02/2023
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages
In this paper, we introduce a novel method for enhancing the effectivene...
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01/28/2023
Composing Task Knowledge with Modular Successor Feature Approximators
Recently, the Successor Features and Generalized Policy Improvement (SF ...
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11/23/2022
Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks
Bayesian deep learning seeks to equip deep neural networks with the abil...
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10/25/2022
In-context Reinforcement Learning with Algorithm Distillation
We propose Algorithm Distillation (AD), a method for distilling reinforc...
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10/25/2021
Self-Consistent Models and Values
Learned models of the environment provide reinforcement learning (RL) ag...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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02/24/2021
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
We study reinforcement learning (RL) with no-reward demonstrations, a se...
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06/26/2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Out-of-training-distribution (OOD) scenarios are a common challenge of l...
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05/28/2020
Uncertainty Evaluation Metric for Brain Tumour Segmentation
In this paper, we develop a metric designed to assess and rank uncertain...
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03/12/2020
Invariant Causal Prediction for Block MDPs
Generalization across environments is critical to the successful applica...
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12/22/2019
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
Evaluation of Bayesian deep learning (BDL) methods is challenging. We of...
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09/12/2019
Reinforcement Learning for Portfolio Management
In this thesis, we develop a comprehensive account of the expressive pow...
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07/02/2019
Generalizing from a few environments in safety-critical reinforcement learning
Before deploying autonomous agents in the real world, we need to be conf...
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06/11/2019
