DomainBed is a suite to test domain generalization algorithms

[TAI 2023] Contrastive Domain Adaptation for Time-Series via Temporal Mixup

Contrastive Adversarial Learning for Multi-Source Time Series Domain Adaptation

Domain Adaptation for Time Series Under Feature and Label Shifts

Code for the paper "Twin Contrastive Learning for Online Clustering" (IJCV 2022)

Code for the paper "Contrastive Clustering" (AAAI 2021)

基于spingboot完成的b2c模式的移动端小程序

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…

[TPAMI 2023] Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification

Unsupervised Domain Adaptation for Time Series Classification

Transfer learning for time series classification

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Benchmarks for Out-of-Distribution Generalization in Time Series Tasks

Code for our CVPR 2022 paper 'Generalized Category Discovery'. Project page: https://www.robots.ox.ac.uk/~vgg/research/gcd/

Beyond Known Clusters: Probe New Prototypes for Efficient Generalized Class Discovery

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

[ICML 2024] A novel, efficient approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

Neighborhood Contrastive Learning for Novel Class Discovery, CVPR 2021

"Learning to Discover Novel Visual Categories via Deep Transfer Clustering" by Kai Han, Andrea Vedaldi, Andrew Zisserman (ICCV 2019)

(ICCV 2023) Parametric Classification for Generalized Category Discovery: A Baseline Study

A list of papers that studies Novel Class Discovery

"Automatically Discovering and Learning New Visual Categories with Ranking Statistics" by Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman (ICLR 2020)

EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

Code for IJCAI-23 Paper "Open-world Semi-supervised Novel Class Discovery"

PyTorch implementation for the paper Class-incremental Novel Class Discovery (ECCV 2022)

PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"

PyCIL: A Python Toolbox for Class-Incremental Learning

Details of the datasets for Few-shot class-incremental audio classification

Implementation of the paper "Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning"

Awesome Incremental Learning