11 Repositories
Python truncated-svd Libraries
Official code for "Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes", CVPR2022
[CVPR 2022] Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, and Cha
Python factor analysis library (PCA, CA, MCA, MFA, FAMD)
Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize
⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co
Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning
isvd Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning If you find this code useful, you may cite us as: @inprocee
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
Distiller is an open-source Python package for neural network compression research.
Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres
Spectral Tensor Train Parameterization of Deep Learning Layers
Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr
T-LOAM: Truncated Least Squares Lidar-only Odometry and Mapping in Real-Time
T-LOAM: Truncated Least Squares Lidar-only Odometry and Mapping in Real-Time The first Lidar-only odometry framework with high performance based on tr
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
An implementation of the 1. Parallel, 2. Streaming, 3. Randomized SVD using MPI4Py
PYPARSVD This implementation allows for a singular value decomposition which is: Distributed using MPI4Py Streaming - data can be shown in batches to
A Python scikit for building and analyzing recommender systems
Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with th