cwang-nus

cwang-nus's Stars

• huggingface/transformers

  🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

  Language:Python133k1.1k15.9k26.5k

• awesomedata/awesome-public-datasets

  A topic-centric list of HQ open datasets.

  60.4k2.3k1139.9k

• state-spaces/mamba

  Mamba SSM architecture

  Language:Python12.8k1015131.1k

• xialeiliu/Awesome-Incremental-Learning

  Awesome Incremental Learning

  3.7k13246565

• cure-lab/LTSF-Linear

  [AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

  Language:Python2k16112439

• ddz16/TSFpaper

  This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

  1.9k6422173

• tim-learn/awesome-test-time-adaptation

  Collection of awesome test-time (domain/batch/instance) adaptation methods

  69318148

• Vision-Intelligence-and-Robots-Group/Best-Incremental-Learning

  An Incremental Learning, Continual Learning, and Life-Long Learning Repository

  540182250

• radarFudan/Awesome-state-space-models

  Collection of papers on state-space models

  52617319

• YuejiangLIU/awesome-source-free-test-time-adaptation

  A curated list of papers in Test-time Adaptation, Test-time Training and Source-free Domain Adaptation

  45812742

• DAMO-DI-ML/NeurIPS2023-One-Fits-All

  The official code for "One Fits All: Power General Time Series Analysis by Pretrained LM (NeurIPS 2023 Spotlight)"

  Language:Python45154463

• BUAABIGSCity/PDFormer

  [AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.

  Language:Python19525734

• uctb/UCTB

  An Open Source Spatio-Temporal Prediction Package

  Language:Python180191142

• thuml/Koopa

  Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

  Language:Python17942223

• deepkashiwa20/DL-Traff-Graph

  [CIKM 2021 Resource Paper] DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction (Graph Part)

  Language:Python1702324

• liuxu77/LargeST

  LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (NeurIPS 2023 DB Track)

  Language:Python1592714

• Echo-Ji/ST-SSL

  ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

  Language:Python14221228

• aikunyi/FreTS

  Official implementation of the paper "Frequency-domain MLPs are More Effective Learners in Time Series Forecasting"

  Language:Python12821122

• XDZhelheim/STAEformer

  [CIKM'23] Official code for our paper "Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting".

  Language:Python12651516

• hughxx/tsf-new-paper-taste

  A code implementation of new papers in the time series forecasting field.

  Language:Python12021118

• LINs-lab/ttab

  [ICML23] On Pitfalls of Test-Time Adaptation

  Language:Python10121510

• liuxu77/UniTime

  UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting (WWW 2024)

  Language:Python662105

• Z-GCNETs/Z-GCNETs

  Language:Python362310

• SUST-reynole/USSFC-Net

  Language:Python33364

• Arthur-Null/SRD

  Official pytorch implementation of Spatial Relation Decomposition method (AAAI 23)

  Language:Python22152

• deepkashiwa20/Urban_Concept_Drift

  [CIKM 2023] MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation

  Language:Jupyter Notebook17112

• KL4805/TransGTR

  Open-source code of TransGTR.

  Language:Python10143

• yousuf907/SIESTA

  PyTorch implementation of the SIESTA algorithm from our TMLR-2023 paper "SIESTA: Efficient Online Continual Learning with Sleep"

  Language:Python102

• XinZhang525/DAC-ML

  This is the code for the paper DAC-ML accepted by ICDM21.

  Language:Python4200

• Urban-Computing/STC-Dropout

  Easy Begun is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout

  Language:Python3112