A resource for learning about Machine learning & Deep Learning

A Collection of Variational Autoencoders (VAE) in PyTorch.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/

[CVPR2020] Adversarial Latent Autoencoders

🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

👁️ 🖼️ 🔥PyTorch Toolbox for Image Quality Assessment, including LPIPS, FID, NIQE, NRQM(Ma), MUSIQ, TOPIQ, NIMA, DBCNN, BRISQUE, PI and more...

State-of-the-art, simple, fast unbounded / large-scale NeRFs.

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

This repository is the official implementation of Disentangling Writer and Character Styles for Handwriting Generation (CVPR 2023)

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

LibCity: An Open Library for Urban Spatial-temporal Data Mining

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)

[CVPR 2022] FaceFormer: Speech-Driven 3D Facial Animation with Transformers

A Pytorch Implementation of "Neural Speech Synthesis with Transformer Network"

[ACL 2024] Official PyTorch code for extracting features and training downstream models with emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation

From scratch implementation of a sparse mixture of experts language model inspired by Andrej Karpathy's makemore :)