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2 Dec 2023 |
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6 Feb 2023 |
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| Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy Optimization |
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5 Jun 2022 |
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2 Mar 2022 |
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14 Feb 2022 |
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17 Nov 2021 |
jaewon-lee-b/lte/models/models.py 44c3aa4c610ea3f7 |
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| Local Texture Estimator for Implicit Representation Function |
17 Nov 2021 |
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| Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution |
30 Oct 2021 |
ml-postech/lisa/models/models.py 44c3aa4c610ea3f7 |
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| Contrastive Reinforcement Learning of Symbolic Reasoning Domains |
16 Jun 2021 |
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26 May 2021 |
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15 Oct 2020 |
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| Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning |
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| Curious Hierarchical Actor-Critic Reinforcement Learning |
7 May 2020 |
knowledgetechnologyuhh/goal_conditioned_RL_baselines/baselines/common/models.py a44574392d168384 |
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| Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning |
9 Mar 2020 |
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| Performative Prediction |
16 Feb 2020 |
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18 Dec 2019 |
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| Influence-Based Multi-Agent Exploration |
12 Oct 2019 |
TonghanWang/EITI-EDTI/baselines/common/models.py a44574392d168384 |
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10 Oct 2019 |
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| RLCard: A Toolkit for Reinforcement Learning in Card Games |
10 Oct 2019 |
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| DiffTaichi: Differentiable Programming for Physical Simulation |
1 Oct 2019 |
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| Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds |
29 Aug 2019 |
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| Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards |
13 Jun 2019 |
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| Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation |
16 May 2019 |
RuohanW/RED/baselines/common/models.py a44574392d168384 |
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| Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning |
7 May 2019 |
seungyulhan/disc/baselines/common/models.py a44574392d168384 |
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| Deep Reinforcement Learning using Genetic Algorithm for Parameter Optimization |
19 Feb 2019 |
aralab-unr/ReinforcementLearningWithGA/baselines/common/models.py a44574392d168384 |
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| Assessing Generalization in Deep Reinforcement Learning |
29 Oct 2018 |
sunblaze-ucb/rl-generalization/sunblaze_envs/registration.py 0c4c9f359acd3c78 |
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MIT (permissive) |
| Pyro: Deep Universal Probabilistic Programming |
18 Oct 2018 |
uber/pyro/pyro/settings.py 4ccde65baa528cbc |
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| PCN: Point Completion Network |
2 Aug 2018 |
wentaoyuan/pcn/kitti_registration.py 079447ff7ae596e5 |
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| Simple random search provides a competitive approach to reinforcement learning |
19 Mar 2018 |
eric-erki/robotics-rl-srl/environments/registry.py 171decf255010ed6 |
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| Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation |
17 Aug 2017 |
openai/baselines/baselines/common/models.py a44574392d168384 |
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| Improved Training of Wasserstein GANs |
31 Mar 2017 |
unicredit/ganzo/src/loss.py 28c0e133abb7a340 |
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| Learning to reinforcement learn |
17 Nov 2016 |
gomerudo/openai-baselines/baselines/common/models.py a44574392d168384 |
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2010-07 (from id) |
scikit-hep/pyhf/src/pyhf/events.py ca0999c2f2915b3a |
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| arXiv:aaai_20297 |
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| arXiv:Xiao_Towards_Progressive_Multi-Frequency_Representation_for_Image_Warping_CVPR_2024_paper |
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| arXiv:Wang_Object_Detection_using_Event_Camera_A_MoE_Heat_Conduction_based_CVPR_2025_paper |
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| arXiv:Han_ABCD_Arbitrary_Bitwise_Coefficient_for_De-Quantization_CVPR_2023_paper |
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