Sparse Optimisation Research Code

Convolution dictionary learning for time-series

Official implementation of PointBeV: A Sparse Approach to BeV Predictions

✨ A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.

This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029

[ICLR 2019] "ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA", by Jialin Liu*, Xiaohan Chen*, Zhangyang Wang and Wotao Yin.

L1-regularized least squares with PyTorch

Face Recognition in real-world images [ICASSP 2017]

Dictionary Learning for image processing

Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper

An implementation of Olshausen and Field (96) in PyTorch

A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions

We introduce a way to extend sparse dictionary learning to deep architectures.

A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.

Embedder with binary sparse distributed representation.

Greedy Adaptive Dictionary (GAD) is a learning algorithm that sets out to find sparse atoms for speech signals.

This repo for the paper titled "SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification"

Python Implementation of Proximal Methods for Hierarchical Sparse Coding

Sparse representation solvers for P0- and P1-problems