Voyageran's starred repositories
BionicReader
A simple bionic text converter that can take a file (pdf, txt, docx), extract the text, and convert it into bionic text.
bionicpython
AI powered library to convert your pdfs and docx to bionic reading format.
stat-learning
Notes and exercise attempts for "An Introduction to Statistical Learning"
stylegan2-pytorch
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
stylegan2-ada-pytorch
StyleGAN2-ADA - Official PyTorch implementation
annotated_deep_learning_paper_implementations
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
UGATIT-pytorch
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
gans-with-pytorch
Various implementations of Generative adversarial networks using Pytorch
denoising-diffusion-pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
BeamerStyleSlides
🌈Beamer风格的幻灯片模板集。包含了PowerPoint和Keynote两套格式。
rime-wenzhounese
基於Rime的溫州話輸入方案規則；基于Rime的温州话输入方案规则（采用沈克成先生-沈迦先生的拼音方案）
LinearRegression-Notes
For sharing purposes
image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Deep-HdrReconstruction
Official PyTorch implementation of "Single Image HDR Reconstruction Using a CNN with Masked Features and Perceptual Loss" (SIGGRAPH 2020)
google-sites-liberation
Fork Version: This is an import/export tool for Google Sites.
Mat_Var_Factor_Model
Code for Statistical Inference for High Dimensional Matrix Variate Factor Model (Chen & Fan, 2021, JASA) in R
SMILEsmileD
open source smile detector haarcascade and associated positive & negative image datasets
Variational-Bayesian-Dictionary-Learning-on-Tensor-Factorization
Bayesian Dictionary Learning on Robust Tubal Transformed Tensor Factorization
ConvDicLearnTensorFactor
Tensor methods have emerged as a powerful paradigm for consistent learning of many latent variable models such as topic models, independent component analysis and dictionary learning. Model parameters are estimated via CP decomposition of the observed higher order input moments. However, in many domains, additional invariances such as shift invariances exist, enforced via models such as convolutional dictionary learning. In this paper, we develop novel tensor decomposition algorithms for parameter estimation of convolutional models. Our algorithm is based on the popular alternating least squares method, but with efficient projections onto the space of stacked circulant matrices. Our method is embarrassingly parallel and consists of simple operations such as fast Fourier transforms and matrix multiplications. Our algorithm converges to the dictionary much faster and more accurately compared to the alternating minimization over filters and activation maps.
learning-q-sharp
微软Q#
paper-reading
深度学习经典、新论文逐段精读