Pinned Repositories
analog-beamforming-v2i
includes DFT codebook
Antenna-Selection-and-Beamforming-with-BandB-and-ML
Machine learning accelerated Branch and Bound for Joint beamforming and antenna selection
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
Awesome-Masked-Autoencoders
A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
DDQN_BeamSelection
Joint Deep Reinforcement Learning and Unfolding: Beam Selection and Precoding for mmWave Multiuser MIMO With Lens Arrays
GNN-Communication-Networks
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
Multi-Armed-Bandits-Papers
"At some point we have to give up and say that's just the way it is. Or, not give up and push on."― Leonard Susskind,
rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
sionna
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
maryamhsnv's Repositories
maryamhsnv/analog-beamforming-v2i
includes DFT codebook
maryamhsnv/Antenna-Selection-and-Beamforming-with-BandB-and-ML
Machine learning accelerated Branch and Bound for Joint beamforming and antenna selection
maryamhsnv/Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
maryamhsnv/DDQN_BeamSelection
Joint Deep Reinforcement Learning and Unfolding: Beam Selection and Precoding for mmWave Multiuser MIMO With Lens Arrays
maryamhsnv/GNN-Communication-Networks
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
maryamhsnv/Multi-Armed-Bandits-Papers
"At some point we have to give up and say that's just the way it is. Or, not give up and push on."― Leonard Susskind,
maryamhsnv/rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
maryamhsnv/sionna
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
maryamhsnv/Awesome-Masked-Autoencoders
A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).
maryamhsnv/Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
maryamhsnv/daily_arxiv
Using GitHub Action to collect paper list with publicly available source code in the daily arxiv
maryamhsnv/few-shot-gnn
maryamhsnv/GNN-in-RS
super_important
maryamhsnv/GNN-Resource-Management
maryamhsnv/GNNetworkingChallenge
RouteNet baseline for the Graph Neural Networking Challenge (https://bnn.upc.edu/challenge/)
maryamhsnv/HybridPrecodingOpt
Optimization algorithms for hybrid precoding in mmWave MIMO systems: Version 1.1.0
maryamhsnv/JointDesigninmmWaveCellFreeNetworks
Submitted paperwork
maryamhsnv/mae
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
maryamhsnv/mmWave-MU-MIMO
The project represents the main code for the proposed cross-layer Dynamic sub-array scheduling for 5G applications, in collaboration with Mathworks inc.
maryamhsnv/multiple_antenna_communications
This repository contains the slides (in Powerpoint and PDF formats) for the course Multiple Antenna Communications, used 2021. Video recordings of all the slides (with voice over by Emil Björnson) can be found on YouTube.
maryamhsnv/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
maryamhsnv/pennylane
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
maryamhsnv/pytorch_geometric
Geometric Deep Learning Extension Library for PyTorch
maryamhsnv/RegGNN
Regression Graph Neural Network (regGNN) for cognitive score prediction.
maryamhsnv/Resilient_RRM_GNN
Implementation code for the paper "Learning Resilient Radio Resource Management Policies with Graph Neural Networks" (IEEE Transactions on Signal Processing)
maryamhsnv/RSTG
maryamhsnv/Sub6-Preds-mmWave
Using sub-6 GHz channels to predict mmWave beams and link blockage.
maryamhsnv/TransNet
This is the PyTorch implementation of the paper "TransNet: Full Attentiodn Network for CSI Feedback in FDD Massive MIMO System". Please read the README.md to help your reproducing.
maryamhsnv/Unrolled-WMMSE
Tensorflow implementation of Unfolding WMMSE using Graph Neural Networks for Efficient Power Allocation
maryamhsnv/Unrolled-WMMSE-for-MU-MIMO
Tensorflow implementation of Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks