Authors' implementation for "Designing Constrained Projections for Compressed Sensing: Mean Errors and Anomalies with Coherence", IEEE GlobalSIP 2018
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Updated
Sep 25, 2018 - MATLAB
Authors' implementation for "Designing Constrained Projections for Compressed Sensing: Mean Errors and Anomalies with Coherence", IEEE GlobalSIP 2018
Light Implementation on Model Compression - BME590-02-Final Project
Presentations I have prepared for different courses and lab seminar throughout my PhD
Minimal Reproducibility Study of (https://arxiv.org/abs/1911.05248). Experiments with Compression of Deep Neural Networks
MATLAB implementation of sparsity-assisted signal denoising and pattern recognition in time-series data
This is the repository for reproducing results in "APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks".
NeurIPS 2019 MicroNet Challenge
Finding Storage- and Compute-Efficient Convolutional Neural Networks
Soft Threshold Weight Reparameterization for Learnable Sparsity
Compact Image Captioning (CoCA) is an open source image captioning project to promote Green Computer Vision, as well as to make image captioning research accessible to universities, research labs and individual practitioners with limited financial resources.
Code Repository for "Orthogonally Weighted Regularization for Rank-Aware Joint Sparse Recovery: Algorithm and Analysis" Authors: A. Petrosyan, K. Pieper, H. Tran
Modern Fortran Numerical Differentiation Library
model compression and optimization for deployment for Pytorch, including knowledge distillation, quantization and pruning.(知识蒸馏,量化,剪枝)
skscope: Sparse-Constrained OPtimization via itErative-solvers
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