ykwangsun

ykwangsun's Stars

• AntixK/PyTorch-VAE

  A Collection of Variational Autoencoders (VAE) in PyTorch.

  Language:Python6.6k43851.1k

• ritheshkumar95/pytorch-vqvae

  Vector Quantized VAEs - PyTorch Implementation

  Language:Python839614138

• rdevon/DIM

  Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"

  Language:Python8062052102

• kakaobrain/rq-vae-transformer

  The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)

  Language:Jupyter Notebook782162385

• MishaLaskin/vqvae

  A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

  Language:Jupyter Notebook6347875

• SingleZombie/DL-Demos

  Demos for deep learning

  Language:Python39455101

• nayuki/Reference-arithmetic-coding

  Clear implementation of arithmetic coding for educational purposes in Java, Python, C++.

  Language:Java3681613105

• Jackson-Kang/Pytorch-VAE-tutorial

  A simple tutorial of Variational AutoEncoders with Pytorch

  Language:Jupyter Notebook3243475

• gtegner/mine-pytorch

  Mutual Information Neural Estimation in Pytorch

  Language:Jupyter Notebook2877655

• YongfeiYan/Gumbel_Softmax_VAE

  PyTorch implementation of a Variational Autoencoder with Gumbel-Softmax Distribution

  Language:Python2022937

• gruberto/DL-ChannelDecoding

  On Deep Learning-based Channel Decoding

  Language:Jupyter Notebook7711669

• duchenzhuang/FSQ-pytorch

  A Pytorch Implementation of Finite Scalar Quantization

  Language:Python73544

• wsxtyrdd/NTSCC_JSAC22

  Language:Python731715

• shaojiawei07/VL-VFE

  Codes for paper "Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Method"

  Language:Python54209

• maybeliuchuan/Task-Oriented-Semantic-Communications

  Journal on Communications

  Language:Python53198

• SJTU-mxtao/semantic-communication-w-codebook

  Pytorch implementation of all the methods in the paper "Improving Learning-Based Semantic Coding Efficiency for Image Transmission via Shared Semantic-Aware Codebook"

  Language:Python49103

• RQC-QApp/polar-codes

  Python implementation of Polar codes

  Language:Python395015

• iconix/pytorch-text-vae

  A conditional variational autoencoder (CVAE) for text

  Language:Python32305

• SJTU-mxtao/Joint-Coding-Modulation-for-Digital-Semantic-Communication

  Language:Python23124

• aprilbian/deepjscc-lplusplus

  Source code for paper deepjscc-l++

  Language:Python20111

• jxmorris12/categorical-vae

  Categorical Variational Auto-encoders in PyTorch

  Language:Jupyter Notebook20316

• paulchen2713/NOMA_DQN

  (Caveats! Dirty Code!!) Solving some Non-Orthogonal Multiple Access (NOMA) resource allocation problem, allocating Tx power properly at downlink to maximize the sum rate, by using DQN

  Language:Python20132

• fdap/Awesome_Semantic_Comm_Sys

  Summary of research works about vision-oriented semantic communication system.

  19211

• changwoolee/isec-deep-jscc

  An official implementation of "Deep Joint Source-Channel Coding with Iterative Source Error Correction"

  Language:Python16101

• psrikanthm/categorical-vae

  Implement Categorical Variational autoencoder using Pytorch

  Language:Python15310

• wsxtyrdd/NTSCC_plus

  Language:Python15142

• ZJU-IICNS-AICOMM/MIMO-Simulation

  This is a python simulation of a MIMO communication system, including M-QAM modulation and demodulation.

  Language:Python15003

• maxjcohen/vqvae

  VQ-VAE implementation in pytorch, supporting EMA and Gumbel trainings. Applicable for images and time series.

  Language:Jupyter Notebook9212

• tushar-ydv/VLC_NOMA

  Non-orthogonal multiple access (NOMA) for Indoor Visible Light Communications. We offer a complete review of PD-NOMA-based VLC systems in this study. In addition, we discuss aspects of the PD-NOMA VLC system restrictions and challenges, such as power allocation, clipping effect, MIMO, and security.

  Language:MATLAB8

• zab0613/UIS_Trade-off

  Language:Python2