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2020 – today
- 2024
[j1]Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio:
Distributional GFlowNets with Quantile Flows. Trans. Mach. Learn. Res. 2024 (2024)- [c28]Zhengqi Gao
, Dinghuai Zhang, Luca Daniel, Duane S. Boning:
NOFIS: Normalizing Flow for Rare Circuit Failure Analysis. DAC 2024: 279:1-279:6 - [c27]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR 2024 - [c26]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. ICLR 2024 - [c25]Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. ICLR 2024 - [c24]Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. ICLR 2024 - [c23]Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. ICML 2024 - [i34]Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu:
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. CoRR abs/2405.16730 (2024) - [i33]Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Josh M. Susskind, Navdeep Jaitly, Shuangfei Zhai:
Improving GFlowNets for Text-to-Image Diffusion Alignment. CoRR abs/2406.00633 (2024) - [i32]George Ma, Emmanuel Bengio, Yoshua Bengio, Dinghuai Zhang:
Baking Symmetry into GFlowNets. CoRR abs/2406.05426 (2024) - [i31]Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K. Yang, Guy Wolf, Doina Precup, Shuangjia Zheng:
EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics. CoRR abs/2410.00327 (2024) - [i30]Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Josh M. Susskind, Shuangfei Zhai:
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation. CoRR abs/2410.08159 (2024) - [i29]Eric Hanchen Jiang, Zhi Zhang, Dinghuai Zhang, Andrew Lizarraga, Chenheng Xu, Yasi Zhang, Siyan Zhao, Zhengjie Xu, Peiyu Yu, Yuer Tang, Deqian Kong, Ying Nian Wu:
DODT: Enhanced Online Decision Transformer Learning through Dreamer's Actor-Critic Trajectory Forecasting. CoRR abs/2410.11359 (2024) - 2023
- [c22]Zhijian Duan, Wenhan Huang, Dinghuai Zhang, Yali Du, Jun Wang, Yaodong Yang, Xiaotie Deng:
Is Nash Equilibrium Approximator Learnable? AAMAS 2023: 233-241 - [c21]Yimu Wang, Dinghuai Zhang, Yihan Wu, Heng Huang, Hongyang Zhang:
Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets. CVPR 2023: 20564-20574 - [c20]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. ICLR 2023 - [c19]Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio:
Generative Augmented Flow Networks. ICLR 2023 - [c18]Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan:
Predictive Inference with Feature Conformal Prediction. ICLR 2023 - [c17]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR 2023 - [c16]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. ICML 2023: 18269-18300 - [c15]Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. ICML 2023: 21715-21729 - [c14]Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio:
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. ICML 2023: 26878-26890 - [c13]Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan:
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS 2023 - [c12]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. UAI 2023: 1628-1638 - [i28]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. CoRR abs/2301.12594 (2023) - [i27]Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio:
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. CoRR abs/2302.01687 (2023) - [i26]Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio:
Distributional GFlowNets with Quantile Flows. CoRR abs/2302.05793 (2023) - [i25]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. CoRR abs/2302.09465 (2023) - [i24]Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan:
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR abs/2305.17010 (2023) - [i23]Yimu Wang, Dinghuai Zhang, Yihan Wu, Heng Huang, Hongyang Zhang:
Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets. CoRR abs/2306.15482 (2023) - [i22]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR abs/2310.02423 (2023) - [i21]Dinghuai Zhang, Ricky Tian Qi Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. CoRR abs/2310.02679 (2023) - [i20]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. CoRR abs/2310.02710 (2023) - [i19]Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woochang Kim, Jinkyoo Park, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. CoRR abs/2310.02823 (2023) - [i18]Mingyang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. CoRR abs/2310.08774 (2023) - [i17]Zhengqi Gao, Dinghuai Zhang, Luca Daniel, Duane S. Boning:
Rare Event Probability Learning by Normalizing Flows. CoRR abs/2310.19167 (2023) - 2022
- [c11]Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville:
Unifying Likelihood-free Inference with Black-box Optimization and Beyond. ICLR 2022 - [c10]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio:
Biological Sequence Design with GFlowNets. ICML 2022: 9786-9801 - [c9]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. ICML 2022: 26412-26428 - [c8]Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala:
Building Robust Ensembles via Margin Boosting. ICML 2022: 26669-26692 - [i16]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. CoRR abs/2202.01361 (2022) - [i15]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio:
Biological Sequence Design with GFlowNets. CoRR abs/2203.04115 (2022) - [i14]Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala:
Building Robust Ensembles via Margin Boosting. CoRR abs/2206.03362 (2022) - [i13]Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, Yoshua Bengio:
Unifying Generative Models with GFlowNets. CoRR abs/2209.02606 (2022) - [i12]Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan:
Predictive Inference with Feature Conformal Prediction. CoRR abs/2210.00173 (2022) - [i11]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. CoRR abs/2210.00580 (2022) - [i10]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR abs/2210.00999 (2022) - [i9]Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio:
Generative Augmented Flow Networks. CoRR abs/2210.03308 (2022) - [i8]Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. CoRR abs/2210.12928 (2022) - 2021
- [c7]Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu:
Neural Approximate Sufficient Statistics for Implicit Models. ICLR 2021 - [c6]David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville:
Out-of-Distribution Generalization via Risk Extrapolation (REx). ICML 2021: 5815-5826 - [c5]Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville:
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML 2021: 12356-12367 - [c4]Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish:
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. NeurIPS 2021: 3438-3450 - [i7]Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville:
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR abs/2106.02890 (2021) - [i6]Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish:
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR abs/2106.06607 (2021) - [i5]Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville:
Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond. CoRR abs/2110.03372 (2021) - 2020
- [c3]Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang:
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective. ICML 2020: 8828-8839 - [c2]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. NeurIPS 2020 - [i4]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. CoRR abs/2002.09169 (2020) - [i3]Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang:
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective. CoRR abs/2008.04254 (2020) - [i2]Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu:
Neural Approximate Sufficient Statistics for Implicit Models. CoRR abs/2010.10079 (2020)
2010 – 2019
- 2019
- [c1]Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong:
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle. NeurIPS 2019: 227-238 - [i1]Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong:
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle. CoRR abs/1905.00877 (2019)
Coauthor Index
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last updated on 2024-12-02 22:27 CET by the dblp team
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