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1155.life

996.ICU 的反向 repo: 11-5-5 工作制 - 工作 11-5-5，生活为先

active-learning-papers

A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.

adacare

ai-job-notes

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

arm

auto-gpt-local

An experimental open-source attempt to make GPT-4 fully autonomous.

autokeras

autokeras-1

AutoML library for deep learning

awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-deep-learning-finetune-experience

This repository not only contains experience about parameter finetune, but also other in-practice experience such as model ensemble (boosting, bagging and stacking) in Kaggle or other competitions.

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

awesome-ensemble-learning

Ensemble learning related books, papers, videos, and toolboxes

awesome-learning-with-label-noise

A curated list of resources for Learning with Noisy Labels

awesome-nas

A curated list of neural architecture search (NAS) resources.

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

awesome_deep_learning_interpretability

深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

bayesgroup.github.io

bayesian-active-learning-pytorch

Implementation of Bayesian NNs in Pytorch (https://arxiv.org/pdf/1703.02910.pdf) (With some help from https://github.com/Riashat/Deep-Bayesian-Active-Learning/))

bayesian-belief-networks

Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.

bayesian-neural-networks

bayesian_neural_network_papers

Papers for Bayesian-NN

bayesiancnn

binarynet.pytorch

Binarized Neural Network (BNN) for pytorch

book

:green_book:我的个人书籍学习和收藏

brain-tumor-segmentation-and-survival-prediction-using-deep-neural-networks

Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of patients through deep neural networks.

cavia

Code for "Fast Context Adaptation via Meta-Learning"

challenge2020_test4

cleanlab

The standard package for machine learning with noisy labels and finding mislabeled data. Works with most datasets and models.

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization. https://poloclub.github.io/cnn-explainer/