GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Last update: Feb 15, 2022

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GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

This is the code to the paper: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery by:

Jonathan Sauder (EPFL)

Martin Genzel (Utrecht University)

Peter Jung (TU Berlin)

An example for how to use this codebase for the Single-Pixel Imaging experiments from the paper is provided in main_singlepixel.py.

Please write us an email in case of questions.

Requirements: torch, torchvision, scipy, numpy, matplotlib, pandas, pywt

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GitHub Repository

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GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Related tags

Overview

GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Owner

This is an official implementation for "Video Swin Transformers".

[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs

We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC).

“英特尔创新大师杯”深度学习挑战赛赛道3：CCKS2021中文NLP地址相关性任务

a Lightweight library for sequential learning agents, including reinforcement learning

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The dataset of tweets pulling from Twitters with keyword: Hydroxychloroquine, location: US, Time: 2020

Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting" by Shu et al.

Run Effective Large Batch Contrastive Learning on Limited Memory GPU

Repo for parser tensorflow(.pb) and tflite(.tflite)

[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.

This repository contains the code to replicate the analysis from the paper "Moving On - Investigating Inventors' Ethnic Origins Using Supervised Learning"

A modification of Daniel Russell's notebook merged with Katherine Crowson's hq-skip-net changes

🙄 Difficult algorithm, Simple code.

Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"

Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

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Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

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GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Related tags

Overview

GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Owner

This is an official implementation for "Video Swin Transformers".

[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs

We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC).

“英特尔创新大师杯”深度学习挑战赛 赛道3：CCKS2021中文NLP地址相关性任务

a Lightweight library for sequential learning agents, including reinforcement learning

A deep learning library that makes face recognition efficient and effective

The dataset of tweets pulling from Twitters with keyword: Hydroxychloroquine, location: US, Time: 2020

Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting" by Shu et al.

Run Effective Large Batch Contrastive Learning on Limited Memory GPU

Repo for parser tensorflow(.pb) and tflite(.tflite)

[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.

This repository contains the code to replicate the analysis from the paper "Moving On - Investigating Inventors' Ethnic Origins Using Supervised Learning"

A modification of Daniel Russell's notebook merged with Katherine Crowson's hq-skip-net changes

🙄 Difficult algorithm, Simple code.

Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"

Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

ArtEmis: Affective Language for Art

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

ilpyt: imitation learning library with modular, baseline implementations in Pytorch

Racing line optimization algorithm in python that uses Particle Swarm Optimization.

“英特尔创新大师杯”深度学习挑战赛赛道3：CCKS2021中文NLP地址相关性任务