Stars
Using GitHub Action to collect paper list with publicly available source code in the daily arxiv
Python library for stochastic numerical optimization
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Pytorch version of NIPS'16 "Learning to learn by gradient descent by gradient descent"
Implementation of NeurIPS 2018 paper "Meta-Gradient Reinforcement Learning"
[NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'
Implementing DeepMind's Fast Reinforcement Learning paper, and adding additional features to generalize the algorithms
Fast version of RL & IL library, work in progress.
This is the COST2100 channel model, a MATLAB implementation of a spatially consistent radio channel model for MIMO and Massive MIMO communication. Originally developed within COST 2100 (http://www.…
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Python code for "Deep Learning for Massive MIMO CSI Feedback"
This is an implementation of ACRNet for results reproduction on COST2100
Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Multiuser MIMO Systems
Code for my publication: Deep Learning Predictive Band Switching in Wireless Networks. Paper accepted for publication to IEEE Transactions in Wireless Communications.
Code of the paper, CLNet: Complex Input Lightweight Neural Network designed for Massive MIMO CSI Feedback
Simulation code for "Unsupervised Deep Learning for Massive MIMO Hybrid Beamforming" by Hamed Hojatian, Jeremy Nadal, Jean-Francois Frigon, Francois Leduc-Primeau, 2020.
Channel Reconstruction Network implemented in PyTorch
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"
Summary of open source code for deep learning models in the field of traffic prediction