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09/14/2023
Beta Diffusion
We introduce beta diffusion, a novel generative modeling method that int...
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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...
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06/01/2023
Preference-grounded Token-level Guidance for Language Model Fine-tuning
Aligning language models (LMs) with preferences is an important problem ...
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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-...
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05/04/2023
AutoML-GPT: Automatic Machine Learning with GPT
AI tasks encompass a wide range of domains and fields. While numerous AI...
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05/01/2023
In-Context Learning Unlocked for Diffusion Models
We present Prompt Diffusion, a framework for enabling in-context learnin...
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04/30/2023
Class-Balancing Diffusion Models
Diffusion-based models have shown the merits of generating high-quality ...
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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...
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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...
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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...
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03/16/2023
Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models
For downstream applications of vision-language pre-trained models, there...
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03/13/2023
DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration
Blind face restoration usually synthesizes degraded low-quality data wit...
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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...
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02/08/2023
A Prototype-Oriented Clustering for Domain Shift with Source Privacy
Unsupervised clustering under domain shift (UCDS) studies how to transfe...
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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...
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10/16/2022
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding
Embedded topic models are able to learn interpretable topics even with l...
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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...
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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...
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09/20/2022
Knowledge-Aware Bayesian Deep Topic Model
We propose a Bayesian generative model for incorporating prior domain kn...
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09/12/2022
Ordinal Graph Gamma Belief Network for Social Recommender Systems
To build recommender systems that not only consider user-item interactio...
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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...
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08/05/2022
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification
Imbalanced data pose challenges for deep learning based classification m...
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06/15/2022
CARD: Classification and Regression Diffusion Models
Learning the distribution of a continuous or categorical response variab...
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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...
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06/14/2022
Probabilistic Conformal Prediction Using Conditional Random Samples
This paper proposes probabilistic conformal prediction (PCP), a predicti...
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06/05/2022
Diffusion-GAN: Training GANs with Diffusion
For stable training of generative adversarial networks (GANs), injecting...
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05/10/2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
Active learning, which effectively collects informative unlabeled data f...
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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...
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02/19/2022
A Regularized Implicit Policy for Offline Reinforcement Learning
Offline reinforcement learning enables learning from a fixed dataset, wi...
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02/19/2022
Truncated Diffusion Probabilistic Models
Employing a forward Markov diffusion chain to gradually map the data to ...
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02/14/2022
Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs
Token-mixing multi-layer perceptron (MLP) models have shown competitive ...
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12/15/2021
Bayesian Graph Contrastive Learning
Contrastive learning has become a key component of self-supervised learn...
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10/27/2021
TopicNet: Semantic Graph-Guided Topic Discovery
Existing deep hierarchical topic models are able to extract semantically...
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10/26/2021
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator
Accurately backpropagating the gradient through categorical variables is...
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10/25/2021
Alignment Attention by Matching Key and Query Distributions
The neural attention mechanism has been incorporated into deep neural ne...
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10/18/2021
Learning Prototype-oriented Set Representations for Meta-Learning
Learning from set-structured data is a fundamental problem that has rece...
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06/30/2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
Hierarchical topic models such as the gamma belief network (GBN) have de...
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06/15/2021
Probabilistic Margins for Instance Reweighting in Adversarial Training
Reweighting adversarial data during training has been recently shown to ...
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06/09/2021
Bayesian Attention Belief Networks
Attention-based neural networks have achieved state-of-the-art results o...
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06/01/2021
Adversarially Adaptive Normalization for Single Domain Generalization
Single domain generalization aims to learn a model that performs well on...
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05/28/2021
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables
Estimating the gradients for binary variables is a task that arises freq...
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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 ...
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04/02/2021
Partition-Guided GANs
Despite the success of Generative Adversarial Networks (GANs), their tra...
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03/06/2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
Dropout has been demonstrated as a simple and effective module to not on...
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12/28/2020
Comparing Probability Distributions with Conditional Transport
To measure the difference between two probability distributions, we prop...
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12/25/2020
Self-supervised Pre-training with Hard Examples Improves Visual Representations
Self-supervised pre-training (SSP) employs random image transformations ...
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10/31/2020
Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference
Efficient modeling of relational data arising in physical, social, and i...
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10/21/2020
Convex Polytope Trees
A decision tree is commonly restricted to use a single hyperplane to spl...
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10/20/2020
Bayesian Attention Modules
Attention modules, as simple and effective tools, have not only enabled ...
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10/02/2020
