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Weijun Xu's Projects

annotated_deep_learning_paper_implementations icon 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, ... 🧠

awesome-conformal-prediction icon awesome-conformal-prediction

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

bayesian-neural-networks icon bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

bayesian-torch icon bayesian-torch

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

beta-nll icon beta-nll

beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022

cbm_codes_open icon cbm_codes_open

This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.

convgp icon convgp

Convolutional Gaussian processes based on GPflow.

deep-learning-in-phm icon deep-learning-in-phm

Deep learning in PHM,Deep learning in fault diagnosis,Deep learning in remaining useful life prediction

deepcgp icon deepcgp

Deep convolutional gaussian processes.

easy-rl icon easy-rl

强化学习中文教程(蘑菇书),在线阅读地址:https://datawhalechina.github.io/easy-rl/

googletest icon googletest

Googletest - Google Testing and Mocking Framework

gpy icon gpy

Gaussian processes framework in python

incertae icon incertae

Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments

interview icon interview

📚 C/C++ 技术面试基础知识总结,包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。

kaggle icon kaggle

Kaggle 项目实战(教程) = 文档 + 代码 + 视频(欢迎参与)

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