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Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks.

, , , , , , , and . ICMLA, page 892-897. IEEE Computer Society, (2016)

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The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning., , , and . NeurIPS, (2020)Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events, , , , , and . Advances in neural information processing systems, (2017)Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets., , , , , , , , and . CoRR, (2016)Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments., and . CoRR, (2019)Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC., , , , , and . CoRR, (2017)Slot Contrastive Networks: A Contrastive Approach for Representing Objects., and . CoRR, (2020)Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks., , , , , , , and . ICMLA, page 892-897. IEEE Computer Society, (2016)Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving., , , , , , , , , and 7 other author(s). IROS, page 8652-8659. IEEE, (2022)Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets., , , , and . CoRR, (2016)ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events., , , , , and . NIPS, page 3402-3413. (2017)