Genegan: Learning object transfiguration and attribute subspace from unpaired data S Zhou, T Xiao, Y Yang, D Feng, Q He, W He
arXiv preprint arXiv:1705.04932, 2017
109 2017 Solving hard ai planning instances using curriculum-driven deep reinforcement learning D Feng, CP Gomes, B Selman
arXiv preprint arXiv:2006.02689, 2020
29 2020 A novel automated curriculum strategy to solve hard sokoban planning instances D Feng, CP Gomes, B Selman
Advances in Neural Information Processing Systems 33, 3141-3152, 2020
21 2020 Training bit fully convolutional network for fast semantic segmentation H Wen, S Zhou, Z Liang, Y Zhang, D Feng, X Zhou, C Yao
arXiv preprint arXiv:1612.00212, 2016
11 2016 A new perspective on building efficient and expressive 3D equivariant graph neural networks Y Du, L Wang, D Feng, G Wang, S Ji, CP Gomes, ZM Ma
Advances in Neural Information Processing Systems 36, 2024
7 2024 Weighted Sampling without Replacement for Deep Top- Classification D Feng, Y Du, CP Gomes, B Selman
International Conference on Machine Learning, 9910-9920, 2023
2023 Deep Combinatorial Reasoning: From Games to Scientific Discovery D Feng
Cornell University, 2023
2023 Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning D Feng, CP Gomes, B Selman
Advances in Neural Information Processing Systems 35, 36295-36307, 2022
2022 Graph Value Iteration D Feng, CP Gomes, B Selman
arXiv preprint arXiv:2209.09608, 2022
2022 The Remarkable Effectiveness of Combining Policy and Value Networks in A*-based Deep RL for AI Planning D Feng, CP Gomes, B Selman
2021