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| PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection |
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9 Aug 2024 |
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| Flexible Tails for Normalizing Flows |
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| What Matters in Transformers? Not All Attention is Needed |
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| Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning |
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| Stabilizing Backpropagation Through Time to Learn Complex Physics |
3 May 2024 |
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21 Apr 2024 |
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| Monitored Markov Decision Processes |
9 Feb 2024 |
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30 Jan 2024 |
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| Attention-Guided Contrastive Role Representations for Multi-Agent Reinforcement Learning |
2023-12 (from id) |
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| AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection |
29 Oct 2023 |
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| CBD: A Certified Backdoor Detector Based on Local Dominant Probability |
26 Oct 2023 |
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6 Oct 2023 |
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| Delving into CLIP latent space for Video Anomaly Recognition |
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| KuaiSim: A Comprehensive Simulator for Recommender Systems |
22 Sep 2023 |
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21 Jul 2023 |
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| Balanced Energy Regularization Loss for Out-of-distribution Detection |
18 Jun 2023 |
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| Decentralized SGD and Average-direction SAM are Asymptotically Equivalent |
5 Jun 2023 |
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4 Jun 2023 |
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2023-02 (from id) |
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| Winning the Lottery Ahead of Time: Efficient Early Network Pruning |
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24 Mar 2022 |
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| Faster Deep Reinforcement Learning with Slower Online Network |
10 Dec 2021 |
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| Conflict-Averse Gradient Descent for Multi-task Learning |
26 Oct 2021 |
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| Continual Semi-Supervised Learning through Contrastive Interpolation Consistency |
14 Aug 2021 |
loribonna/cssl/models/lwf.py bc5d184387cac930 |
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16 Jun 2021 |
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| Adversarial Intrinsic Motivation for Reinforcement Learning |
27 May 2021 |
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18 May 2021 |
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15 Nov 2020 |
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14 Sep 2020 |
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18 Jun 2020 |
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27 Apr 2020 |
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| Coping With Simulators That Don't Always Return |
28 Mar 2020 |
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6 Nov 2019 |
ucr-optml/FedNest/reproduce/fig2.py 97aa6390755cc0a7 |
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| On the Convergence of FedAvg on Non-IID Data |
4 Jul 2019 |
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2 Oct 2018 |
wangjksjtu/rl-perturbed-reward/gym-control/plot.py 414baf4e279c0209 |
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27 Jul 2018 |
sujoyp/wtalc-pytorch/detectionMAP.py 4a6f77bd7b90ba28 |
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MIT (permissive) |
| QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning |
30 Mar 2018 |
nju-rl/acorm/plot.py 30cf9bec8ce2ebf3 |
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26 Feb 2018 |
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6 Nov 2016 |
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| arXiv:136640190 |
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| arXiv:136640190 |
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MIT (permissive) |