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Use rules from Homebrew Cask to scan for leftover files from uninstalled software.
[ICLR2025] Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
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 …
A simple and efficient Mamba implementation in pure PyTorch and MLX.
[KDD 2025] A Multi-Scale Token Mixing Transformer for Irregular Multivariate Time Series Classification
The simplest pytorch implement (100 lines) of "Neural Ordinary Differential Equations" @ NeurIPS 2018 Best Paper.
Python suite to construct benchmark machine learning datasets from the MIMIC-III 💊 clinical database.
[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.
[VLDB 2024] A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
Multi-Dimensional Rail Transit Passenger Flow Prediction
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
猫抓 浏览器资源嗅探扩展 / cat-catch Browser Resource Sniffing Extension
Resources about time series forecasting and deep learning.
Code release of paper "MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting" (ICLR 2023)
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
Official implementation of our ICLR 2023 paper "Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting"
[ACM MM 2024]A Tree-Based Structure-Aware Transformer Decoder for Image-To-Markup Generation
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.