共 50 条
- [1] On the Expressivity of Neural Networks for Deep Reinforcement Learning [J]. 25TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS (AMCIS 2019), 2019,
- [2] On the Expressivity of Neural Networks for Deep Reinforcement Learning [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 119, 2020, 119
- [3] A Transfer Approach Using Graph Neural Networks in Deep Reinforcement Learning [J]. THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 15, 2024, : 16352 - 16360
- [4] Modeling and prediction of protein structure using deep neural networks [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2018, 256
- [5] Transparency and Explanation in Deep Reinforcement Learning Neural Networks [J]. PROCEEDINGS OF THE 2018 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY (AIES'18), 2018, : 144 - 150
- [6] Parameterized Adaptive Controller Design using Reinforcement Learning and Deep Neural Networks [J]. 2022 EIGHTH INDIAN CONTROL CONFERENCE, ICC, 2022, : 121 - 126
- [7] Reinforcement Learning Enhanced Explainer for Graph Neural Networks [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 34 (NEURIPS 2021), 2021, 34
- [8] Modeling Complex Networks Based on Deep Reinforcement Learning [J]. FRONTIERS IN PHYSICS, 2022, 9
- [9] Enhanced gradient learning for deep neural networks [J]. IET IMAGE PROCESSING, 2022, 16 (02) : 365 - 377
- [10] Modeling a System for Monitoring an Object Using Artificial Neural Networks and Reinforcement Learning [J]. 2011 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2011, : 2327 - 2332