Sparse Optimisation Research Code
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Updated
Apr 29, 2024 - Python
Sparse Optimisation Research Code
Convolution dictionary learning for time-series
✨ 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
Official implementation of PointBeV: A Sparse Approach to BeV Predictions
[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
An implementation of Olshausen and Field (96) in PyTorch
Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper
A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.
We introduce a way to extend sparse dictionary learning to deep architectures.
Embedder with binary sparse distributed representation.
Greedy Adaptive Dictionary (GAD) is a learning algorithm that sets out to find sparse atoms for speech signals.
Sparse representation solvers for P0- and P1-problems
Python Implementation of Proximal Methods for Hierarchical Sparse Coding
An unsupervised compressed-sensing technique for fundamental objects selection
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