Fei-Yeh

Fei-Yeh's Stars

• labmlai/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, ... 🧠

  Language:Python55.6k4561325.7k

• TencentARC/GFPGAN

  GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

  Language:Python35.8k5084755.9k

• eriklindernoren/PyTorch-GAN

  PyTorch implementations of Generative Adversarial Networks.

  Language:Python16.4k2201564.1k

• hindupuravinash/the-gan-zoo

  A list of all named GANs!

  Language:Python14.3k567352.5k

• vega/altair

  Declarative statistical visualization library for Python

  Language:Python9.3k1402k793

• open-mmlab/mmagic

  OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

  Language:Jupyter Notebook6.9k977071.1k

• bndw/wifi-card

  📶 Print a QR code for connecting to your WiFi (wificard.io)

  Language:JavaScript6.6k4075466

• probml/pyprobml

  Python code for "Probabilistic Machine learning" book by Kevin Murphy

  Language:Jupyter Notebook6.5k1924561.5k

• YapengTian/Single-Image-Super-Resolution

  A collection of high-impact and state-of-the-art SR methods

  1.8k1101375

• xinychen/awesome-latex-drawing

  Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.

  Language:TeX1.3k372155

• wangkai930418/awesome-diffusion-categorized

  collection of diffusion model papers categorized by their subareas

  1.2k551862

• 52CV/CVPR-2023-Papers

  93116779

• Kenguba/google-access-helper

  谷歌访问助手破解版、谷歌翻墙、谷歌梯子、谷歌梯子扩展工具、谷歌商店访问、Chrome翻墙

  Language:JavaScript8605512262

• lixinustc/Awesome-diffusion-model-for-image-processing

  one summary of diffusion-based image processing, including restoration, enhancement, coding, quality assessment

  61516450

• gchenfc/sci-hub-now

  Free access to academic papers with just a single click! Abolish publishers, long live the open access movement! 🦅

  Language:JavaScript535124561

• Trinkle23897/oi_slides

  我的 OI 课件

  5047193

• ssydasheng/Bayesian_neural_network_papers

  Papers for Bayesian-NN

  31419052

• zsyOAOA/VDNet

  Variational Denoising Network: Toward Blind Noise Modeling and Removal (NeurIPS, 2019) (Pytorch)

  Language:Python2124944

• tiepvupsu/DICTOL

  DICTOL - A Dictionary Learning Toolbox in Matlab and Python

  Language:MATLAB18712689

• max19951001/Free-shared-Spatiotemporal-method-of-remote-sensing-

  spatiotemporal fusion method

  Language:Python1374045

• MIRALab-USTC/KGE-DURA

  The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.

  Language:Python50349

• ricardoborsoi/unmixing_spectral_variability

  A complete toolbox for spectral unmixing with spectral variability

  Language:MATLAB461013

• peiyunh/mat-vae

  A MATLAB implementation of Auto-Encoding Variational Bayes

  Language:Matlab447322

• NaiyangGuan/Truncated-Cauchy-Non-Negative-Matrix-Factorization

  Non-negative matrix factorization (NMF) minimizes the euclidean distance between the data matrix and its low rank approximation, and it fails when applied to corrupted data because the loss function is sensitive to outliers. In this paper, we propose a Truncated CauchyNMF loss that handle outliers by truncating large errors, and develop a Truncated CauchyNMF to robustly learn the subspace on noisy datasets contaminated by outliers. We theoretically analyze the robustness of Truncated CauchyNMF comparing with the competing models and theoretically prove that Truncated CauchyNMF has a generalization bound which converges at a rate of order O(lnn/n‾‾‾‾‾√) , where n is the sample size. We evaluate Truncated CauchyNMF by image clustering on both simulated and real datasets. The experimental results on the datasets containing gross corruptions validate the effectiveness and robustness of Truncated CauchyNMF for learning robust subspaces.

  Language:MATLAB12102

• qw245/FUMI

  Q. Wei, J. M. Bioucas-Dias, N. Dobigeon, J-Y. Tourneret, M. Chen and S. Godsill, ''Multi-band image fusion based on spectral unmixing,'' IEEE Trans. Geosci. and Remote Sens., to appear.

  Language:Matlab10203

• ricardoborsoi/FuVarRelease

  codes for the paper "Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability", IEEE TIP 2020

  Language:MATLAB10102

• 201power/bpjdl

  Li He, Hairong Qi, Russell Zaretzki, "Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution", CVPR 2013

  Language:Matlab5100

• cprevost4/HSR_Software

  Language:MATLAB4203

• A-man032/ComputerVision

  研究生的科研记录，目前研究方向是计算机视觉。

  Language:MATLAB210

• bsantraigi/EEG-Signal-Processing-Kaggle

  Language:MATLAB120