← Authors

Mingyuan Zhou

126 papers · 2009–2025 · 13 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (13) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) πŸ—ΊοΈ Taxonomy Completionist (24) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (8) πŸƒ Academic Marathon (16) 🐺 Lone Wolf (3) 🏠 Conference Loyalist (41) 🀝 Dynamic Duo (38) 🧬 Topic Evolution πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (34) πŸ† Keyword Champion (3) πŸ“ˆ Trend Setter ⚑ Prolific Year (8) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (90) πŸ’Ž Century Club (126) πŸ”₯ Unstoppable (12)

Conferences

NIPS (41) ICML (26) ICLR (23) AISTATS (14) CVPR (9) JMLR (3) ACL (2) ICCV (2) UAI (2) EMNLP (1) IJCAI (1) IJCNLP (1) NAACL (1)

Top co-authors

Bo Chen (38) Huangjie Zheng (17) Zhibin Duan (16) Chaojie Wang (15) Zhendong Wang (15) Shujian Zhang (13) Hao Zhang (11) Dongsheng Wang (10) wenchao chen (9) He Zhao (8)

Research topics

Probability (1)

Keywords

variational inference (19) topic model (14) bayesian inference (11) gibbs sampling (11) topic modeling (8) generative model (8) nonparametric bayesian (7) diffusion model (7) latent representation (6) variational autoencoder (6) reinforcement learning (5) policy gradient (5) uncertainty quantification (5) count datum (5) bayesian nonparametrics (5) bayesian learning (4) document representation (4) variance reduction (4) representation learning (4) hierarchical model (4)

Papers

Advancing Graph Generation through Beta Diffusion ICLR 2025
DRL: Decomposed Representation Learning for Tabular Anomaly Detection ICLR 2025
Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation ICLR 2025
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models ICLR 2025
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors CVPR 2025
KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding ACL 2025
OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation ICML 2025
One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation ICML 2025
Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step ICLR 2025
Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer ICLR 2025
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection ICML 2024
OmniMotionGPT: Animal Motion Generation with Limited Data CVPR 2024
UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures CVPR 2024
Improving Unsupervised Hierarchical Representation with Reinforcement Learning CVPR 2024
Long-tailed Diffusion Models with Oriented Calibration ICLR 2024
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting ICLR 2024
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling ICLR 2024
Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models UAI 2024
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation ICML 2024
Switchable Decision: Dynamic Neural Generation Networks ICML 2024
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference ICML 2024
Pseudo-Private Data Guided Model Inversion Attacks NIPS 2024
Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning NIPS 2024
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning ICLR 2023
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems ICLR 2023
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models NIPS 2023
Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates JMLR 2023
Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023
DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration CVPR 2023
Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes NIPS 2023
Diffusion-GAN: Training GANs with Diffusion ICLR 2023
Class-Balancing Diffusion Models CVPR 2023
PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification ICCV 2023
Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory NIPS 2023
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling ICML 2023
Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process ICML 2023
Prototype-oriented unsupervised anomaly detection for multivariate time series ICML 2023
POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models ICML 2023
Uncertainty-aware Unsupervised Video Hashing AISTATS 2023
In-Context Learning Unlocked for Diffusion Models NIPS 2023
Preference-grounded Token-level Guidance for Language Model Fine-tuning NIPS 2023
Beta Diffusion NIPS 2023
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders ICLR 2023
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data ICLR 2022
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport NIPS 2022
A Variational Edge Partition Model for Supervised Graph Representation Learning NIPS 2022
Knowledge-Aware Bayesian Deep Topic Model NIPS 2022
A Unified Framework for Alternating Offline Model Training and Policy Learning NIPS 2022
CARD: Classification and Regression Diffusion Models NIPS 2022
Alleviating "Posterior Collapse'' in Deep Topic Models via Policy Gradient NIPS 2022
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification NIPS 2022
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding NIPS 2022
Learning Prototype-oriented Set Representations for Meta-Learning ICLR 2022
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings ICLR 2022
Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection ICML 2022
Bayesian Deep Embedding Topic Meta-Learner ICML 2022
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning ICML 2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness NAACL 2022
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator NIPS 2021
Alignment Attention by Matching Key and Query Distributions NIPS 2021
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NIPS 2021
EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering ACL 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training NIPS 2021
A Prototype-Oriented Framework for Unsupervised Domain Adaptation NIPS 2021
Bayesian Attention Belief Networks ICML 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021
Adversarially Adaptive Normalization for Single Domain Generalization CVPR 2021
Polarimetric Helmholtz Stereopsis ICCV 2021
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables ICML 2021
TopicNet: Semantic Graph-Guided Topic Discovery NIPS 2021
Convex Polytope Trees NIPS 2021
Graph Gamma Process Linear Dynamical Systems AISTATS 2021
Hyperbolic graph embedding with enhanced semi-implicit variational inference. AISTATS 2021
EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering IJCNLP 2021
Partition-Guided GANs CVPR 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module ICLR 2021
Meta-Learning without Memorization ICLR 2020
Variational Autoencoders for Sparse and Overdispersed Discrete Data AISTATS 2020
Friendly Topic Assistant for Transformer Based Abstractive Summarization EMNLP 2020
Mutual Information Gradient Estimation for Representation Learning ICLR 2020
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation ICLR 2020
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling ICLR 2020
Bayesian Attention Modules NIPS 2020
Implicit Distributional Reinforcement Learning NIPS 2020
Bidirectional Convolutional Poisson Gamma Dynamical Systems NIPS 2020
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network NIPS 2020
Recurrent Hierarchical Topic-Guided RNN for Language Generation ICML 2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020
Thompson Sampling via Local Uncertainty ICML 2020
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator UAI 2020
Switching Poisson Gamma Dynamical Systems IJCAI 2020
Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification AISTATS 2020
Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020
Discrete Action On-Policy Learning with Action-Value Critic AISTATS 2020
Poisson-Randomized Gamma Dynamical Systems NIPS 2019
Variational Graph Recurrent Neural Networks NIPS 2019
Locally Private Bayesian Inference for Count Models ICML 2019
Convolutional Poisson Gamma Belief Network ICML 2019
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables ICML 2019
Deep Topic Models for Multi-label Learning AISTATS 2019
Semi-Implicit Graph Variational Auto-Encoders NIPS 2019
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks ICLR 2019
Semi-Implicit Variational Inference ICML 2018
Inter and Intra Topic Structure Learning with Word Embeddings ICML 2018
Nonparametric Bayesian sparse graph linear dynamical systems AISTATS 2018
Parsimonious Bayesian deep networks NIPS 2018
Dirichlet belief networks for topic structure learning NIPS 2018
Masking: A New Perspective of Noisy Supervision NIPS 2018
Deep Poisson gamma dynamical systems NIPS 2018
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression JMLR 2018
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling ICLR 2018
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data NIPS 2018
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks NIPS 2018
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC ICML 2017
Poisson-Gamma dynamical systems NIPS 2016
Augmentable Gamma Belief Networks JMLR 2016
Rotational Crossed-Slit Light Field CVPR 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
The Poisson Gamma Belief Network NIPS 2015
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices AISTATS 2015
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction AISTATS 2015
Beta-Negative Binomial Process and Exchangeable οΏΌRandom Partitions for Mixed-Membership Modeling NIPS 2014
Beta-Negative Binomial Process and Poisson Factor Analysis AISTATS 2012
Augment-and-Conquer Negative Binomial Processes NIPS 2012
Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations NIPS 2009