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← Authors

Dinghuai Zhang

29 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5)
πŸƒ Academic Marathon (6) πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🀝 Dynamic Duo (20) πŸ‘‘ Triple Crown πŸ’Ž Century Club (29) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (7) ⚑ Prolific Year (10) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (76)

Conferences

ICLR (12) ICML (10) NIPS (4) CVPR (2) UAI (1)

Top co-authors

Yoshua Bengio (20) Aaron Courville (9) Nikolay Malkin (8) Ling Pan (6) Zhanxing Zhu (4) Moksh Jain (4) Salem Lahlou (3) Jinkyoo Park (3) Emmanuel Bengio (3) Taeyoung Yun (3)

Keywords

generative flow network (6) out-of-distribution generalization (3) variational inference (3) adversarial robustness (3) domain generalization (3) probabilistic modeling (3) amortized inference (3) reinforcement learning (2) generative model (2) invariant risk minimization (2) adversarial perturbation (2) adversarial training (2) energy-based model (2) adversarial attack (2) game theory (1) ensemble learning (1) lottery ticket hypothesis (1) stochastic processes (1) prompt engineering (1) representation learning (1)

Papers

Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation CVPR 2025 Denoising Autoregressive Transformers for Scalable Text-to-Image Generation ICLR 2025 Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets ICLR 2025 Delta-AI: Local objectives for amortized inference in sparse graphical models ICLR 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets ICML 2024 Local Search GFlowNets ICLR 2024 PhyloGFN: Phylogenetic inference with generative flow networks ICLR 2024 Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization ICLR 2024 Stochastic Generative Flow Networks UAI 2023 Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets NIPS 2023 Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets CVPR 2023 Predictive Inference with Feature Conformal Prediction ICLR 2023 Latent State Marginalization as a Low-cost Approach for Improving Exploration ICLR 2023 GFlowNets and variational inference ICLR 2023 Generative Augmented Flow Networks ICLR 2023 A theory of continuous generative flow networks ICML 2023 GFlowOut: Dropout with Generative Flow Networks ICML 2023 Better Training of GFlowNets with Local Credit and Incomplete Trajectories ICML 2023 Generative Flow Networks for Discrete Probabilistic Modeling ICML 2022 Building Robust Ensembles via Margin Boosting ICML 2022 Unifying Likelihood-free Inference with Black-box Optimization and Beyond ICLR 2022 Biological Sequence Design with GFlowNets ICML 2022 Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization NIPS 2021 Out-of-Distribution Generalization via Risk Extrapolation (REx) ICML 2021 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML 2021 Neural Approximate Sufficient Statistics for Implicit Models ICLR 2021 Informative Dropout for Robust Representation Learning: A Shape-bias Perspective ICML 2020 Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework NIPS 2020 You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle NIPS 2019