Caffe for Sparse and Low-rank Deep Neural Networks

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…

Pytorch implementation of preconditioned stochastic gradient descent (affine group preconditioner, low-rank approximation preconditioner and more)

Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising, ICCV 2017.

Fine-tuning of diffusion models

LoRA (Low-Rank Adaptation) inspector for Stable Diffusion

VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.

A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays

Pytorch implementation of Factorizer.

Tensorflow implementation of preconditioned stochastic gradient descent

HiCMA: Hierarchical Computations on Manycore Architectures

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

[ICLR 2022] Code for paper "Exploring Extreme Parameter Compression for Pre-trained Language Models"(https://arxiv.org/abs/2205.10036)

Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019

Methods for label-free mass spectrometry proteomics

Solver in the low-rank tensor train format with cross approximation approach for the multidimensional Fokker-Planck equation

Convolutive Matrix Factorization in Julia

PyTorch implementation of low-rank factorization (LRF) methods for data compression

Dense Matrix Market