Mingyuan Zhou
Professor
Works on Bayesian statistics and deep generative models, including diffusion model distillation and probabilistic inference.
Mingyuan Zhou's lab at UT Austin works on probabilistic & causal inference, generative & foundation models and image & video generation. 58 papers since 2023, 15 at top venues, mostly ICLR and TMLR. 9 PhD students. 16 alumni. Applications close .
At a glance
- papers, 2023–2026
- 15/ year
- at T1 venues
- 26%
- PhD students
- 9
- MS students
- 0
- alumni listed
- 16
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 8 · collecting
- 14 papers2025 · T1 1
- 13 papers2024 · T1 3
- 23 papers2023 · T1 3
T1 venuesOtherVenues: ICLR, TMLR, ICML, TNNLS, CVPR
Research focuspaper titles that use each topic's words
- Generative & foundation models15 papers
- Image & video generation11 papers
- Probabilistic & causal inference7 papers
- distillation7 papers
- bayesian statistics0 papers
Paper list
From the lab homepage.
20268 papers
- TPAMI (T1)A non-negative deep VAE: the generalized gamma belief network
- ICLR (T1)Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling (opens in a new tab)
- ICLR (T1)Controllable diffusion-based generation for multi-channel biological data (opens in a new tab)
- TNNLS (T1)Disentangled Generative Graph Representation Learning
- ICLR (T1)EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing (opens in a new tab)
- ICML (T1)Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling (opens in a new tab)
- ICML (T1)REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge (opens in a new tab)
- TNNLS (T1)Rethinking Topic Modeling With Information Bottleneck Principle
202514 papers
- ICLR : International Conference on Learning RepresentationsAdvancing Graph Generation through Beta Diffusion (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsAdversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsDRL: Decomposed Representation Learning for Tabular Anomaly Detection (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsEnhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer (opens in a new tab)
- NeurIPS2025: Neural Information Processing SystemsGenerative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting (opens in a new tab)
- NeurIPS2025: Neural Information Processing SystemsGenerative Model Inversion Through the Lens of the Manifold Hypothesis (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsGuided Score Identity Distillation for Data-Free One-Step Text-to-Image Generation (opens in a new tab)
- NeurIPS2025: Neural Information Processing SystemsImproving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay (opens in a new tab)
- Findings of ACLKodcode: A diverse, challenging, and verifiable synthetic dataset for coding
- ICML : International Conference on Machine LearningOmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
- ICML : International Conference on Machine LearningOne-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsScore Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models (opens in a new tab)
202413 papers
- ICML : International Conference on Machine LearningA Dense Reward View on Aligning Text-to-Image Diffusion with Preference (opens in a new tab)
- Current Opinion in Solid State and Materials ScienceAdvancing materials science through next-generation machine learning
- NeurIPS : Neural Information Processing SystemsDiffusion Policies creating a Trust Region for Offline Reinforcement Learning (opens in a new tab)
- TMLR (T1)Hashing with Uncertainty Quantification via Sampling-based Hypothesis Testing (opens in a new tab)
- CVPR (T1)Improving Unsupervised Hierarchical Representation with Reinforcement Learning (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsLearning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsLong-tailed Diffusion Models with Oriented Calibration (opens in a new tab)
- UAI (T1)Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models (opens in a new tab)
- NeurIPS : Neural Information Processing SystemsPseudo-Private Data Guided Model Inversion Attacks (opens in a new tab)
- ICML : International Conference on Machine LearningScore identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation (opens in a new tab)
- ICML : International Conference on Machine LearningSwitchable Decision: Dynamic Neural Generation Networks (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsTransformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting (opens in a new tab)
202323 papers
- ICML : International Conference on Machine LearningBayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process (opens in a new tab)
- Cell SystemsBayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment (opens in a new tab)
- NeurIPS : Neural Information Processing SystemsBeta Diffusion (opens in a new tab)
- CVPR : Conference on Computer Vision and Pattern RecognitionClass-Balancing Diffusion Models (opens in a new tab)
- NeurIPS : Neural Information Processing SystemsContext-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
- TMLR (T1)Contrastive Attraction and Contrastive Repulsion for Representation Learning (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsDiffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsDiffusion-GAN: Training GANs with Diffusion (opens in a new tab)
- CVPR : Conference on Computer Vision and Pattern RecognitionDR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration (opens in a new tab)
- ICLR : International Conference on Learning RepresentationsFantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-Oriented Dialogue Systems (opens in a new tab)
- NeurIPS : Neural Information Processing SystemsFew-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
- TASLP (T1)Hierarchical Topic-Aware Contextualized Transformers
Where alumni went16 listed
Apply to UT AustinFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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