Zhangyang Wang

research

∙ 09/04/2023

Safe and Robust Watermark Injection with a Single OoD Image

Training a high-performance deep neural network requires large amounts o...

0 Shuyang Yu, et al. ∙

research

∙ 08/22/2023

Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts

Cross-scene generalizable NeRF models, which can directly synthesize nov...

0 Wenyan Cong, et al. ∙

research

∙ 08/19/2023

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Sparsely-gated Mixture of Expert (MoE), an emerging deep model architect...

0 Yihua Zhang, et al. ∙

research

∙ 08/17/2023

How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?

Pruning has emerged as a powerful technique for compressing deep neural ...

0 Gregory Holste, et al. ∙

research

∙ 08/11/2023

INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing

An increasing number of researchers are finding use for nth-order gradie...

0 Stefan Abi-Karam, et al. ∙

research

∙ 08/01/2023

Doubly Robust Instance-Reweighted Adversarial Training

Assigning importance weights to adversarial data has achieved great succ...

0 Daouda Sow, et al. ∙

research

∙ 07/20/2023

Physics-Driven Turbulence Image Restoration with Stochastic Refinement

Image distortion by atmospheric turbulence is a stochastic degradation, ...

0 Ajay Jaiswal, et al. ∙

research

∙ 07/20/2023

Reference-based Painterly Inpainting via Diffusion: Crossing the Wild Reference Domain Gap

Have you ever imagined how it would look if we placed new objects into p...

0 Dejia Xu, et al. ∙

research

∙ 07/05/2023

Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities

Recently, zero-shot (or training-free) Neural Architecture Search (NAS) ...

0 Guihong Li, et al. ∙

research

∙ 06/29/2023

FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude

Whole-body biometric recognition is an important area of research due to...

0 Feng Liu, et al. ∙

research

∙ 06/24/2023

H_2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models

Large Language Models (LLMs), despite their recent impressive accomplish...

0 Zhenyu Zhang, et al. ∙

research

∙ 06/18/2023

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

Graphs are omnipresent and GNNs are a powerful family of neural networks...

0 Ajay Jaiswal, et al. ∙

research

∙ 06/18/2023

Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models

Large pre-trained transformers have been receiving explosive attention i...

0 Ajay Jaiswal, et al. ∙

research

∙ 06/13/2023

Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images

The accurate estimation of six degrees-of-freedom (6DoF) object poses is...

0 Panwang Pan, et al. ∙

research

∙ 06/06/2023

The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter

Large pre-trained transformers are show-stealer in modern-day deep learn...

0 Ajay Jaiswal, et al. ∙

research

∙ 05/30/2023

Dynamic Sparsity Is Channel-Level Sparsity Learner

Sparse training has received an upsurging interest in machine learning d...

1 Lu Yin, et al. ∙

research

∙ 05/30/2023

Are Large Kernels Better Teachers than Transformers for ConvNets?

This paper reveals a new appeal of the recently emerged large-kernel Con...

4 Tianjin Huang, et al. ∙

research

∙ 05/30/2023

Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts

Computer vision researchers are embracing two promising paradigms: Visio...

0 Rishov Sarkar, et al. ∙

research

∙ 05/29/2023

Towards Constituting Mathematical Structures for Learning to Optimize

Learning to Optimize (L2O), a technique that utilizes machine learning t...

0 Jialin Liu, et al. ∙

research

∙ 05/25/2023

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

Text-to-image (T2I) research has grown explosively in the past year, owi...

0 Xingqian Xu, et al. ∙

research

∙ 05/25/2023

POPE: 6-DoF Promptable Pose Estimation of Any Object, in Any Scene, with One Reference

Despite the significant progress in six degrees-of-freedom (6DoF) object...

0 Zhiwen Fan, et al. ∙

research

∙ 05/12/2023

MMG-Ego4D: Multi-Modal Generalization in Egocentric Action Recognition

In this paper, we study a novel problem in egocentric action recognition...

0 Xinyu Gong, 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

∙ 04/28/2023

Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation

For a complicated algorithm, its implementation by a human programmer us...

0 Wenqing Zheng, 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

∙ 04/12/2023

AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection

The short-form videos have explosive popularity and have dominated the n...

1 Wentao Zhu, et al. ∙

research

∙ 04/06/2023

Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

Graph neural networks (GNNs) have been widely applied to learning over g...

0 Haotao Wang, et al. ∙

research

∙ 03/30/2023

Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models

The unlearning problem of deep learning models, once primarily an academ...

0 Eric Zhang, et al. ∙

research

∙ 03/30/2023

PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models

Image editing using diffusion models has witnessed extremely fast-paced ...

0 Vidit Goel, et al. ∙

research

∙ 03/23/2023

Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Recent text-to-video generation approaches rely on computationally heavy...

0 Levon Khachatryan, et al. ∙

research

∙ 03/03/2023

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Sparse Neural Networks (SNNs) have received voluminous attention predomi...

0 Shiwei Liu, et al. ∙

research

∙ 03/02/2023

Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers

Despite their remarkable achievement, gigantic transformers encounter si...

0 Tianlong Chen, et al. ∙

research

∙ 03/02/2023

Learning to Grow Pretrained Models for Efficient Transformer Training

Scaling transformers has led to significant breakthroughs in many domain...

0 Peihao Wang, et al. ∙

research

∙ 02/28/2023

M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation

Learning to Optimize (L2O) has drawn increasing attention as it often re...

0 Junjie Yang, et al. ∙

research

∙ 02/27/2023

You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction

Link prediction is central to many real-world applications, but its perf...

0 Wenqing Zheng, et al. ∙

research

∙ 02/27/2023

Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations

Recently, both Contrastive Learning (CL) and Mask Image Modeling (MIM) d...

0 Ziyu Jiang, et al. ∙

research

∙ 02/24/2023

Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?

Given a robust model trained to be resilient to one or multiple types of...

0 Ruisi Cai, et al. ∙

research

∙ 02/22/2023

Learning to Generalize Provably in Learning to Optimize

Learning to optimize (L2O) has gained increasing popularity, which autom...

0 Junjie Yang, et al. ∙

research

∙ 02/06/2023

Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers

This article does not propose any novel algorithm or new hardware for sp...

0 Shiwei Liu, et al. ∙

research

∙ 01/26/2023

Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations

In the United States, primary open-angle glaucoma (POAG) is the leading ...

0 Mingquan Lin, et al. ∙

research

∙ 01/01/2023

Theoretical Characterization of How Neural Network Pruning Affects its Generalization

It has been observed in practice that applying pruning-at-initialization...

0 Hongru Yang, et al. ∙

research

∙ 01/01/2023

Sharper analysis of sparsely activated wide neural networks with trainable biases

This work studies training one-hidden-layer overparameterized ReLU netwo...

0 Hongru Yang, et al. ∙

research

∙ 12/30/2022

Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search

Learning efficient and interpretable policies has been a challenging tas...

0 Wenqing Zheng, et al. ∙

research

∙ 12/06/2022

Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances

Deep neural networks (DNNs) have rapidly become a de facto choice for me...

0 Ajay Jaiswal, et al. ∙

research

∙ 12/03/2022

StegaNeRF: Embedding Invisible Information within Neural Radiance Fields

Recent advances in neural rendering imply a future of widespread visual ...

0 Chenxin Li, et al. ∙

research

∙ 11/29/2022

NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views

Virtual reality and augmented reality (XR) bring increasing demand for 3...

0 Dejia Xu, et al. ∙

research

∙ 11/28/2022

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets

Recent works have impressively demonstrated that there exists a subnetwo...

12 Tianjin Huang, et al. ∙

research

∙ 11/23/2022

Search Behavior Prediction: A Hypergraph Perspective

Although the bipartite shopping graphs are straightforward to model sear...

0 Yan Han, et al. ∙

research

∙ 11/17/2022

AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training

Neural Radiance Fields (NeRFs) are a powerful representation for modelin...

0 Yifan Jiang, et al. ∙

research

∙ 11/15/2022

Versatile Diffusion: Text, Images and Variations All in One Diffusion Model

The recent advances in diffusion models have set an impressive milestone...

0 Xingqian Xu, et al. ∙

Zhangyang Wang

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