Abstract: Matrix operators are fundamental to various applications, particularly in deep learning. While early models relied on dense operations, techniques like pruning have introduced sparsity, ...

Note: The project requires an NVIDIA GPU with CUDA support. The code is tested on Ubuntu 20.04 with CUDA 12.1 and PyTorch 2.3.1. Windows system is strongly ...

Official repository for the AAAI2025 paper Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding ...

Abstract: General sparse matrix-matrix multiplication (SpGEMM) is a fundamental computational method with wide-ranging applications in scientific simulations, machine learning, and image processing.