Convolution dictionary learning for time-series
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Updated
Sep 4, 2024 - Python
Convolution dictionary learning for time-series
✨ A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.
Sparse coding in PyTorch via the Locally Competitive Algorithm (LCA)
Sparse Optimisation Research Code
This repo for the paper titled "SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification"
PyTorch implementation, with CUDA support, of the sparse coding algorithm based on the paper by Olshausen and Field (1997).
Official implementation of PointBeV: A Sparse Approach to BeV Predictions
Image denoising with sparse coding through K-SVD
Sparse representation solvers for P0- and P1-problems
Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper
Early stages of incorporating self-supervised with algorithm unrolling. Code was written as part of a master's thesis (60 ECTS) at Aalborg University, Denmark.
L1-regularized least squares with PyTorch
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
Iterative winners-take-all algorithm
We introduce a way to extend sparse dictionary learning to deep architectures.
[ICLR 2019] "ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA", by Jialin Liu*, Xiaohan Chen*, Zhangyang Wang and Wotao Yin.
Embedder with binary sparse distributed representation.
Transform-Invariant Non-Negative Matrix Factorization
Master's thesis about sparse approximation and dictionary learning using Cloud K-SVD for image denoising. Results show that the algorithm is able to learn sparse representations of signal vectors from distributed data samples in a heterogeneous network setup.
Dictionary Learning for image processing
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