Ali-Ai

shaili-joon

AutoEncoder-Based-Communication-System

Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

autoencoder-for-the-Physical-Layer

Using Keras to validate the simulation results according to Paper : "An Introduction to Deep Learning for the Physical Layer"

D-AMP_Toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

Deep-Learning-for-the-Physical-Layer

PyTorch implementation for part of paper "An Introduction to Deep Learning for the Physical Layer" by Kenta Iwasaki on behalf of Gram.AI.

deep-opt-auctions

Implementation of Optimal Auctions through Deep Learning

deep-rl-tensorflow

TensorFlow implementation of Deep Reinforcement Learning papers

DeepMIMO-codes

DeepMIMO dataset and codes for mmWave and massive MIMO applications

DynamicMultiChannelRL

Contains Implementation of Paper " S Wang, H Liu, P H Gomes, and B Krishnamachari ; Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks"

keras-rl

Deep Reinforcement Learning for Keras.

LDAMP_based-Channel-estimation

This code is for the following paper: H. He, C. Wen, S. Jin, and G. Y. Li, “Deep learning-based channel estimation for beamspace mmwave massive MIMO systems,” IEEE Wireless Commun. Lett., vol. 7, no. 5, pp. 852–855, Oct. 2018.

myGitTst

This is my first test repository on Git :).

Paper-with-Code-of-Wireless-communication-Based-on-DL

无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL

py-radio-autoencoder

Python implementation of autoencoder based radio system

Python_CsiNet

Python code for "Deep Learning for Massive MIMO CSI Feedback"

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.