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01/26/2021
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
Although deep reinforcement learning has led to breakthroughs in many di...
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03/10/2020
The MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors: A Retrospective
To facilitate research in the direction of sample-efficient reinforcemen...
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03/10/2020
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning
To facilitate research in the direction of sample-efficient reinforcemen...
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10/03/2019
On Universal Approximation by Neural Networks with Uniform Guarantees on Approximation of Infinite Dimensional Maps
The study of universal approximation of arbitrary functions f: X→Y by ne...
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07/29/2019
MineRL: A Large-Scale Dataset of Minecraft Demonstrations
The sample inefficiency of standard deep reinforcement learning methods ...
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04/22/2019
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors
Though deep reinforcement learning has led to breakthroughs in many diff...
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02/13/2018
On Characterizing the Capacity of Neural Networks using Algebraic Topology
The learnability of different neural architectures can be characterized ...
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