b'Mingyuan Zhou'

research

∙ 09/14/2023

Beta Diffusion

We introduce beta diffusion, a novel generative modeling method that int...

0 Mingyuan Zhou, et al. ∙

research

∙ 07/18/2023

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification

Multi-label image classification is a prediction task that aims to ident...

0 Miaoge Li, et al. ∙

research

∙ 06/01/2023

Preference-grounded Token-level Guidance for Language Model Fine-tuning

Aligning language models (LMs) with preferences is an important problem ...

0 Shentao Yang, et al. ∙

research

∙ 05/28/2023

Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling

Learning to denoise has emerged as a prominent paradigm to design state-...

0 Tianqi Chen, et al. ∙

research

∙ 05/04/2023

AutoML-GPT: Automatic Machine Learning with GPT

AI tasks encompass a wide range of domains and fields. While numerous AI...

0 Shujian Zhang, et al. ∙

research

∙ 05/01/2023

In-Context Learning Unlocked for Diffusion Models

We present Prompt Diffusion, a framework for enabling in-context learnin...

0 Zhendong Wang, et al. ∙

research

∙ 04/30/2023

Class-Balancing Diffusion Models

Diffusion-based models have shown the merits of generating high-quality ...

0 Yiming Qin, et al. ∙

research

∙ 04/29/2023

POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models

Through prompting, large-scale pre-trained models have become more expre...

0 Korawat Tanwisuth, et al. ∙

research

∙ 04/25/2023

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

Diffusion models are powerful, but they require a lot of time and data t...

0 Zhendong Wang, et al. ∙

research

∙ 04/11/2023

Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond

Although text-to-image diffusion models have made significant strides in...

0 Mohammadreza Armandpour, et al. ∙

research

∙ 03/16/2023

Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models

For downstream applications of vision-language pre-trained models, there...

0 Xinyang Liu, et al. ∙

research

∙ 03/13/2023

DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration

Blind face restoration usually synthesizes degraded low-quality data wit...

0 Zhixin Wang, et al. ∙

research

∙ 02/20/2023

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

When learning task-oriented dialogue (ToD) agents, reinforcement learnin...

0 Yihao Feng, et al. ∙

research

∙ 02/08/2023

A Prototype-Oriented Clustering for Domain Shift with Source Privacy

Unsupervised clustering under domain shift (UCDS) studies how to transfe...

0 Korawat Tanwisuth, et al. ∙

research

∙ 01/11/2023

Generative-Contrastive Learning for Self-Supervised Latent Representations of 3D Shapes from Multi-Modal Euclidean Input

We propose a combined generative and contrastive neural architecture for...

0 Chengzhi Wu, et al. ∙

research

∙ 10/16/2022

HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding

Embedded topic models are able to learn interpretable topics even with l...

0 Yishi Xu, et al. ∙

research

∙ 10/12/2022

A Unified Framework for Alternating Offline Model Training and Policy Learning

In offline model-based reinforcement learning (offline MBRL), we learn a...

0 Shentao Yang, et al. ∙

research

∙ 10/09/2022

Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport

Few-shot classification aims to learn a classifier to recognize unseen c...

0 Dandan Guo, et al. ∙

research

∙ 09/20/2022

Knowledge-Aware Bayesian Deep Topic Model

We propose a Bayesian generative model for incorporating prior domain kn...

0 Dongsheng Wang, et al. ∙

research

∙ 09/12/2022

Ordinal Graph Gamma Belief Network for Social Recommender Systems

To build recommender systems that not only consider user-item interactio...

0 Dongsheng Wang, et al. ∙

research

∙ 08/12/2022

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Offline reinforcement learning (RL), which aims to learn an optimal poli...

0 Zhendong Wang, et al. ∙

research

∙ 08/05/2022

Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification

Imbalanced data pose challenges for deep learning based classification m...

0 Dandan Guo, et al. ∙

research

∙ 06/15/2022

CARD: Classification and Regression Diffusion Models

Learning the distribution of a continuous or categorical response variab...

0 Xizewen Han, et al. ∙

research

∙ 06/14/2022

Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning

Offline reinforcement learning (RL) extends the paradigm of classical RL...

0 Shentao Yang, et al. ∙

research

∙ 06/14/2022

Probabilistic Conformal Prediction Using Conditional Random Samples

This paper proposes probabilistic conformal prediction (PCP), a predicti...

0 Zhendong Wang, et al. ∙

research

∙ 06/05/2022

Diffusion-GAN: Training GANs with Diffusion

For stable training of generative adversarial networks (GANs), injecting...

0 Zhendong Wang, et al. ∙

research

∙ 05/10/2022

ALLSH: Active Learning Guided by Local Sensitivity and Hardness

Active learning, which effectively collects informative unlabeled data f...

0 Shujian Zhang, et al. ∙

research

∙ 03/03/2022

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

A topic model is often formulated as a generative model that explains ho...

0 Dongsheng Wang, et al. ∙

research

∙ 02/19/2022

A Regularized Implicit Policy for Offline Reinforcement Learning

Offline reinforcement learning enables learning from a fixed dataset, wi...

0 Shentao Yang, et al. ∙

research

∙ 02/19/2022

Truncated Diffusion Probabilistic Models

Employing a forward Markov diffusion chain to gradually map the data to ...

0 Huangjie Zheng, et al. ∙

research

∙ 02/14/2022

Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs

Token-mixing multi-layer perceptron (MLP) models have shown competitive ...

0 Huangjie Zheng, et al. ∙

research

∙ 12/15/2021

Bayesian Graph Contrastive Learning

Contrastive learning has become a key component of self-supervised learn...

0 Arman Hasanzadeh, et al. ∙

research

∙ 10/27/2021

TopicNet: Semantic Graph-Guided Topic Discovery

Existing deep hierarchical topic models are able to extract semantically...

2 Zhibin Duan, et al. ∙

research

∙ 10/26/2021

CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator

Accurately backpropagating the gradient through categorical variables is...

0 Alek Dimitriev, et al. ∙

research

∙ 10/25/2021

Alignment Attention by Matching Key and Query Distributions

The neural attention mechanism has been incorporated into deep neural ne...

0 Shujian Zhang, et al. ∙

research

∙ 10/18/2021

Learning Prototype-oriented Set Representations for Meta-Learning

Learning from set-structured data is a fundamental problem that has rece...

0 Dandan Guo, et al. ∙

research

∙ 06/30/2021

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network

Hierarchical topic models such as the gamma belief network (GBN) have de...

0 Zhibin Duan, et al. ∙

research

∙ 06/15/2021

Probabilistic Margins for Instance Reweighting in Adversarial Training

Reweighting adversarial data during training has been recently shown to ...

0 Qizhou Wang, et al. ∙

research

∙ 06/09/2021

Bayesian Attention Belief Networks

Attention-based neural networks have achieved state-of-the-art results o...

0 Shujian Zhang, et al. ∙

research

∙ 06/01/2021

Adversarially Adaptive Normalization for Single Domain Generalization

Single domain generalization aims to learn a model that performs well on...

8 Xinjie Fan, et al. ∙

research

∙ 05/28/2021

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables

Estimating the gradients for binary variables is a task that arises freq...

0 Alek Dimitriev, et al. ∙

research

∙ 05/10/2021

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning

Observing a set of images and their corresponding paragraph-captions, a ...

5 Dandan Guo, et al. ∙

research

∙ 04/02/2021

Partition-Guided GANs

Despite the success of Generative Adversarial Networks (GANs), their tra...

0 Mohammadreza Armandpour, et al. ∙

research

∙ 03/06/2021

Contextual Dropout: An Efficient Sample-Dependent Dropout Module

Dropout has been demonstrated as a simple and effective module to not on...

28 Xinjie Fan, et al. ∙

research

∙ 12/28/2020

Comparing Probability Distributions with Conditional Transport

To measure the difference between two probability distributions, we prop...

6 Huangjie Zheng, et al. ∙

research

∙ 12/25/2020

Self-supervised Pre-training with Hard Examples Improves Visual Representations

Self-supervised pre-training (SSP) employs random image transformations ...

0 Chunyuan Li, et al. ∙

research

∙ 10/31/2020

Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference

Efficient modeling of relational data arising in physical, social, and i...

0 Ali Lotfi Rezaabad, et al. ∙

research

∙ 10/21/2020

Convex Polytope Trees

A decision tree is commonly restricted to use a single hyperplane to spl...

0 Mohammadreza Armandpour, et al. ∙

research

∙ 10/20/2020

Bayesian Attention Modules

Attention modules, as simple and effective tools, have not only enabled ...

0 Xinjie Fan, et al. ∙

research

∙ 10/02/2020

MCMC-Interactive Variational Inference

Leveraging well-established MCMC strategies, we propose MCMC-interactive...

0 Quan Zhang, et al. ∙

Mingyuan Zhou

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