chamwen

chamwen's Stars

• mli/paper-reading

  深度学习经典、新论文逐段精读

  27.5k73202.5k

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook23.1k2452.6k3.3k

• amusi/CVPR2024-Papers-with-Code

  CVPR 2024 论文和开源项目合集

  18.5k2922022.6k

• wilsonfreitas/awesome-quant

  A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

  Language:Python18.5k703692.7k

• dkozlov/awesome-knowledge-distillation

  Awesome Knowledge Distillation

  3.5k1138495

• thuml/Transfer-Learning-Library

  Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

  Language:Python3.5k49202561

• parrt/dtreeviz

  A python library for decision tree visualization and model interpretation.

  Language:Jupyter Notebook3k46208337

• 52CV/CVPR-2021-Papers

  2.5k6621314

• HobbitLong/RepDistiller

  [ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

  Language:Python2.2k1757401

• geatpy-dev/geatpy

  Evolutionary algorithm toolbox and framework with high performance for Python

  Language:Python2k46375727

• AberHu/Knowledge-Distillation-Zoo

  Pytorch implementation of various Knowledge Distillation (KD) methods.

  Language:Python1.6k2317270

• CuriousAI/mean-teacher

  A state-of-the-art semi-supervised method for image recognition

  Language:Python1.6k5759336

• easezyc/deep-transfer-learning

  A collection of implementations of deep domain adaptation algorithms

  Language:Python897937205

• yxgeee/MMT

  [ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.

  Language:Python473104372

• CDTrans/CDTrans

  [ICLR2022] CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

  Language:Python32052039

• yu4u/mixup-generator

  An implementation of "mixup: Beyond Empirical Risk Minimization"

  Language:Jupyter Notebook2858847

• thuml/LogME

  Code release for "LogME: Practical Assessment of Pre-trained Models for Transfer Learning" (ICML 2021) and Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs (JMLR 2022)

  Language:Python20552418

• sebastianruder/learn-to-select-data

  Code for Learning to select data for transfer learning with Bayesian Optimization

  Language:Python17011643

• ChrisAllenMing/Mixup_for_UDA

  Implementation of Adversarial Domain Adaptation with Domain Mixup (AAAI 2020 Oral).

  Language:Python1626824

• mboudiaf/TIM

  (NeurIPS 2020) Transductive Information Maximization for Few-Shot Learning https://arxiv.org/abs/2008.11297

  Language:Python11961420

• FengHZ/KD3A

  Here is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".

  Language:Python1103412

• hou-yz/DA_visualization

  [CVPR2021] "Visualizing Adapted Knowledge in Domain Transfer". Visualization for domain adaptation. #explainable-ai

  Language:Python983514

• Albert0147/NRC_SFDA

  Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

  Language:Python72259

• liyunsheng13/DRT

  Language:Python654109

• daoyuan98/MDDA

  Implementation of paper multi-source distilling domain adaptation

  Language:Python527413

• microsoft/metric-transfer.pytorch

  Deep Metric Transfer for Label Propagation with Limited Annotated Data

  Language:Jupyter Notebook497219

• dfreer15/DeepEEGDataAugmentation

  Code for processing EEG data with Riemannian and deep learning-based classifiers. Additionally provides methods for data augmentation including intentionally imbalancing a dataset, and appending modified data to the training set.

  Language:Python27015

• tntek/N2DCX

  Official implementation for [N2DCX] Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation

  Language:Python20100

• Wang-Xiaodong1899/SSHT

  "SSHT" (Semi-supervised Source Hypothesis Transfer.)

  Language:Python17100

• aryanasadianuoit/Distilling-Knowledge-via-Intermediate-Classifiers

  Distilling Knowledge via Intermediate Classifiers

  Language:Python15107