Підписатись
Dinghuai Zhang 张鼎怀
Dinghuai Zhang 张鼎怀
Інші іменаDinghuai Zhang
Microsoft Research / Mila
Підтверджена електронна адреса в mila.quebec - Домашня сторінка
Назва
Посилання
Посилання
Рік
Out-of-distribution generalization via risk extrapolation (rex)
D Krueger, E Caballero, JH Jacobsen, A Zhang, J Binas, D Zhang, ...
ICML 2021 Long talk, 2020
10052020
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
D Zhang, T Zhang, Y Lu, Z Zhu, B Dong
NeurIPS 2019; arXiv preprint arXiv:1905.00877, 2019
4922019
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
K Ahuja, E Caballero, D Zhang, JC Gagnon-Audet, Y Bengio, I Mitliagkas, ...
NeurIPS 2021 spotlight; arXiv preprint arXiv:2106.06607, 2021
2842021
Biological Sequence Design with GFlowNets
M Jain, E Bengio, AH Garcia, J Rector-Brooks, BFP Dossou, C Ekbote, ...
ICML 2022; arXiv preprint arXiv:2203.04115, 2022
1792022
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
B Shi, D Zhang, Q Dai, Z Zhu, Y Mu, J Wang
ICML 2020, 2020
1242020
Generative Flow Networks for Discrete Probabilistic Modeling
D Zhang, N Malkin, Z Liu, A Volokhova, A Courville, Y Bengio
ICML 2022; arXiv preprint arXiv:2202.01361, 2022
1042022
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?
D Zhang, K Ahuja, Y Xu, Y Wang, A Courville
ICML 2021 long talk; arXiv preprint arXiv:2106.02890, 2021
1032021
A theory of continuous generative flow networks
S Lahlou, T Deleu, P Lemos, D Zhang, A Volokhova, A Hernández-García, ...
ICML 2023; arXiv preprint arXiv:2301.12594, 2023
852023
GFlowNets and variational inference
N Malkin, S Lahlou, T Deleu, X Ji, E Hu, K Everett, D Zhang, Y Bengio
ICLR 2023; arXiv preprint arXiv:2210.00580, 2022
832022
Black-box certification with randomized smoothing: A functional optimization based framework
D Zhang, M Ye, C Gong, Z Zhu, Q Liu
NeurIPS 2020, 2020
772020
Neural Approximate Sufficient Statistics for Implicit Models
Y Chen*, D Zhang*, M Gutmann, A Courville, Z Zhu
ICLR 2021 spotlight; arXiv preprint arXiv:2010.10079, 2020
722020
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets
D Zhang, H Dai, N Malkin, A Courville, Y Bengio, L Pan
NeurIPS 2023 spotlight; arXiv preprint arXiv:2305.17010, 2023
67*2023
Better training of gflownets with local credit and incomplete trajectories
L Pan, N Malkin, D Zhang, Y Bengio
ICML 2023; arXiv preprint arXiv:2302.01687, 2023
612023
Generative Augmented Flow Networks
L Pan, D Zhang, A Courville, L Huang, Y Bengio
ICLR 2023 spotlight; arXiv preprint arXiv:2210.03308, 2022
422022
Unifying Generative Models with GFlowNets and Beyond
D Zhang, RTQ Chen, N Malkin, Y Bengio
ICML 2022 Beyond Bayes workshop; arXiv preprint arXiv:2209.02606, 2022
402022
Stochastic Generative Flow Networks
L Pan, D Zhang, M Jain, L Huang, Y Bengio
UAI 2023 spotlight; arXiv preprint arXiv:2302.09465, 2023
322023
Diffusion generative flow samplers: Improving learning signals through partial trajectory optimization
D Zhang, RTQ Chen, CH Liu, A Courville, Y Bengio
ICLR 2024; arXiv preprint arXiv:2310.02679, 2023
312023
Unifying Likelihood-free Inference with Black-box Optimization and Beyond
D Zhang, J Fu, Y Bengio, A Courville
ICLR 2022 spotlight; arXiv preprint arXiv:2110.03372, 2021
272021
Local Search GFlowNets
M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park
ICLR 2024 spotlight; arXiv preprint arXiv:2310.02710, 2023
262023
Predictive Inference with Feature Conformal Prediction
J Teng, C Wen, D Zhang, Y Bengio, Y Gao, Y Yuan
ICLR 2023; arXiv preprint arXiv:2210.00173, 2022
252022
У даний момент система не може виконати операцію. Спробуйте пізніше.
Статті 1–20