Mingyuan Zhou

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