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microsoft/ClimaX

0
View on GitHub↗
701 stars·108 forks·Python·MIT·4 viewsmicrosoft.github.io/ClimaX↗

ClimaX

This repository contains code accompanying the paper ClimaX: A foundation model for weather and climate.

Features

  • Spatio-Temporal Models - Foundation model for weather and climate forecasting.

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Frequently asked questions

What does microsoft/climax do?

This repository contains code accompanying the paper ClimaX: A foundation model for weather and climate.

What are the main features of microsoft/climax?

The main features of microsoft/climax are: Spatio-Temporal Models.

What are some open-source alternatives to microsoft/climax?

Open-source alternatives to microsoft/climax include: dmlc/dgl — DGL is a Python library for building and training graph neural networks. It functions as a graph message passing… davidham3/astgcn — Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN). gmu-ggs-nsf-abm-research/mobility-trends — A collection of python scripts that uses Safe-Graphs social distancing data to calculate the decrease in… liuxu77/largest — This is the official repository of our NeurIPS 2023 DB Track paper LargeST: A Benchmark Dataset for Large-Scale… sutdcv/sutd-trafficqa — A challenging Video Question Answering (VQA) Benchmark based on real-world traffic scenes. tolicwang/deepst — 本代码使用Tensorflow 1.5 重构自项目:https://github.com/lucktroy/DeepST.

Open-source alternatives to ClimaX

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  • dmlc/dgldmlc avatar

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    DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks

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  • davidham3/astgcnDavidham3 avatar

    Davidham3/ASTGCN

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    Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN)

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  • gmu-ggs-nsf-abm-research/mobility-trendsgmu-ggs-nsf-abm-research avatar

    gmu-ggs-nsf-abm-research/mobility-trends

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    A collection of python scripts that uses Safe-Graphs social distancing data to calculate the decrease in median-non-home-swell-time from 2019 to 2020 in response to COVID-19.

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  • liuxu77/largestliuxu77 avatar

    liuxu77/LargeST

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    This is the official repository of our NeurIPS 2023 DB Track paper LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. LargeST comprises four sub-datasets, each characterized by a different number of sensors. The biggest one is California (CA), including a total number of 8,600…

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See all 6 alternatives to ClimaX→