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all-of-statistics

Self-study on Larry Wasserman's "All of Statistics"

annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

cmw-net

coldl

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

meta-weight-net

NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

meta-weight-net_code-optimization

A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.

mlc

Meta Label Correction for Noisy Label Learning

ms-code-104

multitransformer

Transformer and MultiTransformer layers for stock volatility forecasting purposes

nonstationary_transformers

Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415

pmg-progressive-multi-granularity-training

Code release for Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches (ECCV2020)

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorch-tutorial-2nd

《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。

ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch