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Resources about time series forecasting and deep learning.
TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers
https://github.com/fahim-sikder/TransFusion
1.Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement
code https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/D3VAE
2. Towards Long-Term Time-Series Forecasting: Feature, Pattern, and Distribution
code https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/Conformer
ClaSP - Time Series Segmentation
https://github.com/ermshaua/time-series-segmentation-benchmark
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
https://github.com/huckiyang/Voice2Series-Reprogramming
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning
https://github.com/floft/calda
tsaug
tsaug is a Python package for time series augmentation.
Unable to access https://neuralprophet.com/html/index.html, use https://github.com/ourownstory/neural_prophet to replace.
Diffusion Models for Time Series Applications: A Survey
https://github.com/deel-ai/puncc
Puncc is a python library for predictive uncertainty quantification using conformal prediction.
If you also find this useful, can you add this feature?
Also, I noticed that you added resources for anomaly detection. Here, I want to share a repository DeepOD under development.
By the way, will submitting a paper on anomaly detection have any conflicts with time series forecasting?
Conformal prediction interval for dynamic time-series
https://github.com/hamrel-cxu/EnbPI
Sequential Predictive Conformal Inference
https://github.com/hamrel-cxu/SPCI-code
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications
https://github.com/dongtsi/DeepAID
Time-Series Aware Precision and Recall for Anomaly Detection: Considering Variety of Detection Result and Addressing Ambiguous Labeling
https://github.com/saurf4ng/eTaPR
FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection
https://github.com/jlidw/FluxEV
Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization
https://github.com/eBay/RANSynCoders
Machine learning for transportation data imputation and prediction
transdim
A Python package to discover stochastic differential equations from time series data
PyDaddy
pyclustering is a Python, C++ data mining library
pyclustering
Unsupervised Representation Learning for Time Series: A Review
https://github.com/mqwfrog/ULTS
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion
https://github.com/aurelien-renault/Automatic-Feature-Engineering-for-TSC
DEEPTSF: CODELESS MACHINE LEARNING OPERATIONS FOR TIME SERIES FORECASTING
https://github.com/I-NERGY/DeepTSF
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach
https://github.com/agustdd/floss
I noticed two repositories summed up with method models. There are some papers and codes for time series. You might be able to add some new articles from here.Awesome-Diffusion-Models and awesome-neural-ode.
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