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06/04/2023
For SALE: State-Action Representation Learning for Deep Reinforcement Learning
In the field of reinforcement learning (RL), representation learning is ...
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05/09/2023
Policy Gradient Methods in the Presence of Symmetries and State Abstractions
Reinforcement learning on high-dimensional and complex problems relies o...
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04/28/2023
MUDiff: Unified Diffusion for Complete Molecule Generation
We present a new model for generating molecular data by combining discre...
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03/31/2023
Accelerating exploration and representation learning with offline pre-training
Sequential decision-making agents struggle with long horizon tasks, sinc...
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04/19/2022
Behind the Machine's Gaze: Biologically Constrained Neural Networks Exhibit Human-like Visual Attention
By and large, existing computational models of visual attention tacitly ...
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09/08/2021
Where Did You Learn That From? Surprising Effectiveness of Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning
While significant research advances have been made in the field of deep ...
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05/27/2021
AndroidEnv: A Reinforcement Learning Platform for Android
We introduce AndroidEnv, an open-source platform for Reinforcement Learn...
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03/05/2021
Training a First-Order Theorem Prover from Synthetic Data
A major challenge in applying machine learning to automated theorem prov...
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11/18/2020
Gradient Starvation: A Learning Proclivity in Neural Networks
We identify and formalize a fundamental gradient descent phenomenon resu...
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12/11/2019
Marginalized State Distribution Entropy Regularization in Policy Optimization
Entropy regularization is used to get improved optimization performance ...
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07/21/2018
Safe Option-Critic: Learning Safety in the Option-Critic Architecture
Designing hierarchical reinforcement learning algorithms that induce a n...
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09/16/2016
