cwang-nus's Stars
hughxx/tsf-new-paper-taste
A code implementation of new papers in the time series forecasting field.
BradyFU/Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
takuseno/d3rlpy
An offline deep reinforcement learning library
gengdd/Awesome-Time-Series-Spatio-Temporal
Awesome Time-Series and Spatio-Temporal Related
SJTU-DMTai/qlib
This forked repo additionally includes our DoubleAdapt (KDD'23) and MASTER (AAAI'24) for re-experiment.
yuqinie98/PatchTST
An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
xiyuanzh/time-series-papers
An up-to-date list of time-series related papers in AI venues.
cwang-nus/PRNet
aimagelab/mammoth
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning
THUMNLab/awesome-graph-ood
Papers about out-of-distribution generalization on graphs.
optimass/continual_learning_papers
Relevant papers in Continual Learning
GestaltCogTeam/BasicTS
A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.
HKUDS/GraphST
[ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
zeke-xie/deep-learning-dynamics-paper-list
This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.
khundman/telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Prabhat1808/CrimePrediction
Addressing the problem of predicting crime occurrence based on historic records
salesforce/fsnet
BaiTheBest/DRAIN
GitHub Repo for ICLR 2023 Paper "Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks"
john-x-jiang/meta_ssm
Repository for ICLR 2023 work, "Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting"
thuml/Time-Series-Library
A Library for Advanced Deep Time Series Models.
LukasHedegaard/continual-transformers
Official Pytorch Implementation for "Continual Transformers: Redundancy-Free Attention for Online Inference" [ICLR 2023]
HyunWookL/PM-MemNet
PattonYu/CUFAR
yongduosui/CAL
[KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua.
ZhiningLiu1998/awesome-imbalanced-learning
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切:论文、代码、框架与库
qingsongedu/time-series-transformers-review
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
ray-project/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
tianyu0207/IGD
Official code for 'Deep One-Class Classification via Interpolated Gaussian Descriptor' [AAAI 2022 Oral]
yfzhang114/Generalization-Causality
关于domain generalization,domain adaptation,causality,robutness,prompt,optimization,generative model各式各样研究的阅读笔记
apache/singa
a distributed deep learning platform