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27 Feb 2025 |
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| Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning |
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1 Oct 2024 |
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MIT (permissive) |
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MIT (permissive) |
| Compositional Human-Scene Interaction Synthesis with Semantic Control |
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| Learning Sparse Nonlinear Dynamics via Mixed-Integer Optimization |
1 Jun 2022 |
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| Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods |
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| Is Policy Learning Overrated?: Width-Based Planning and Active Learning for Atari |
30 Sep 2021 |
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MIT (permissive) |
| Diverse Image Generation via Self-Conditioned GANs |
18 Jun 2020 |
stevliu/self-conditioned-gan/metrics.py c7976bd4f8c4e9f6 |
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| Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks |
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| Dual Policy Distillation |
7 Jun 2020 |
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6 Nov 2019 |
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6 Oct 2019 |
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MIT (permissive) |
| ALBERT: A Lite BERT for Self-supervised Learning of Language Representations |
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| ALBERT: A Lite BERT for Self-supervised Learning of Language Representations |
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MIT (permissive) |
| Compositionality decomposed: how do neural networks generalise? |
22 Aug 2019 |
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MIT (permissive) |
| Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning |
7 May 2019 |
seungyulhan/disc/baselines/bench/monitor.py 404244405c7fd238 |
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| The StarCraft Multi-Agent Challenge |
11 Feb 2019 |
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| Transferring Knowledge across Learning Processes |
3 Dec 2018 |
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Apache-2.0 (permissive) |
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27 Nov 2018 |
SsnL/dataset-distillation/utils/io.py 062128c654a29276 |
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MIT (permissive) |
| QUOTA: The Quantile Option Architecture for Reinforcement Learning |
5 Nov 2018 |
Kchu/DeepRL_CK/Distributional_RL/monitor.py 404244405c7fd238 |
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6 Jun 2018 |
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Apache-2.0 (permissive) |
| Task-based End-to-end Model Learning in Stochastic Optimization |
13 Mar 2017 |
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| Task-based End-to-end Model Learning in Stochastic Optimization |
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locuslab/e2e-model-learning/power_sched/plot.py a9861553a6f58c1b |
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2 Feb 2017 |
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MIT (permissive) |
| Generative Adversarial Imitation Learning |
10 Jun 2016 |
Techget/gail-tf-sc2/gailtf/baselines/bench/monitor.py 0c09148efe18bf06 |
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MIT (permissive) |
| A QCQP Approach to Triangulation |
2012-07 (from id) |
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