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PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Minimal-boilerplate web apps from Python functions.

『ゼロから作る Deep Learning ❹』(O'Reilly Japan, 2022)

Main repository of SageMath

HPy: a better API for Python

A Python library that helps data scientists to infer causation rather than observing correlation.

Repository of a data modeling and analysis tool based on Bayesian networks

List of papers, code and experiments using deep learning for time series forecasting

Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)

TradingAgents: Multi-Agents LLM Financial Trading Framework

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-s…

Snap7 is an open source, 32/64 bit, multi-platform Ethernet communication suite for interfacing natively with Siemens S7 PLCs.

MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing

Code for our VLDB'22 paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

(ICLR 2025) TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling

MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting (AAAI2024)

This checklist is designed to help you systematically prepare and polish academic papers for top conferences and journals (e.g., ICML, NeurIPS, CVPR). It incorporates widely recommended best practi…

PDE-Transformer is a neural network architecture designed to efficiently process and predict the evolution of physical systems described by partial differential equations.

The official repository of the PRformer paper: "PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting." This work is developed by the Lab of Professor Feiping Nie (feip…

[KDD'24] Official code for our paper "Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting".

Resources about time series forecasting and deep learning.

INFS4205 Type I Individual Project: Taxi Trajectory Analysis (2025)

Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)

Fast local thickness in 3D and 2D

Time Series Analysis and Forecasting in Python

Code for NeurIPS'24 paper 'Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization'