Dinghuai Zhang
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
26
Venues
5
Active years
2020–2025
Best venue rank
A*
Where they publish
Papers
26 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation. | Taeyoung Yun, Dinghuai Zhang, Jinkyoo Park, Ling Pan |
| 2025 | ICLR | Denoising Autoregressive Transformers for Scalable Text-to-Image Generation. | Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai |
| 2025 | ICLR | Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. | Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang |
| 2024 | DAC | NOFIS: Normalizing Flow for Rare Circuit Failure Analysis. | Zhengqi Gao, Dinghuai Zhang, Luca Daniel, Duane S. Boning |
| 2024 | ICLR | Delta-AI: Local objectives for amortized inference in sparse graphical models. | Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio |
| 2024 | ICLR | Local Search GFlowNets. | Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park |
| 2024 | ICLR | Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. | Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio |
| 2024 | ICLR | PhyloGFN: Phylogenetic inference with generative flow networks. | Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio |
| 2024 | ICML | Learning to Scale Logits for Temperature-Conditional GFlowNets. | Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio |
| 2023 | CVPR | Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets. | Yimu Wang, Dinghuai Zhang, Yihan Wu, Heng Huang, Hongyang Zhang |
| 2023 | ICLR | GFlowNets and variational inference. | Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio |
| 2023 | ICLR | Generative Augmented Flow Networks. | Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio |
| 2023 | ICLR | Predictive Inference with Feature Conformal Prediction. | Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan |
| 2023 | ICLR | Latent State Marginalization as a Low-cost Approach for Improving Exploration. | Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen |
| 2023 | ICML | A theory of continuous generative flow networks. | Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernndez-Garca, Lna Nhale Ezzine, Yoshua Bengio, Nikolay Malkin |
| 2023 | ICML | GFlowOut: Dropout with Generative Flow Networks. | 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 |
| 2023 | ICML | Better Training of GFlowNets with Local Credit and Incomplete Trajectories. | Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio |
| 2023 | UAI | Stochastic Generative Flow Networks. | Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio |
| 2022 | ICLR | Unifying Likelihood-free Inference with Black-box Optimization and Beyond. | Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville |
| 2022 | ICML | Biological Sequence Design with GFlowNets. | Moksh Jain, Emmanuel Bengio, Alex Hernndez-Garca, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio |
| 2022 | ICML | Generative Flow Networks for Discrete Probabilistic Modeling. | Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio |
| 2022 | ICML | Building Robust Ensembles via Margin Boosting. | Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala |
| 2021 | ICLR | Neural Approximate Sufficient Statistics for Implicit Models. | Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu |
| 2021 | ICML | Out-of-Distribution Generalization via Risk Extrapolation (REx). | David Krueger, Ethan Caballero, Jrn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rmi Le Priol, Aaron C. Courville |
| 2021 | ICML | Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? | Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville |
| 2020 | ICML | Informative Dropout for Robust Representation Learning: A Shape-bias Perspective. | Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang |