geogismx

geogismx's Stars

• google-deepmind/graphcast

  Language:Python5.5k92100669

• Doriandarko/maestro

  A framework for Claude Opus to intelligently orchestrate subagents.

  Language:Python4.2k7645650

• williamleif/GraphSAGE

  Representation learning on large graphs using stochastic graph convolutions.

  Language:Python3.4k77166845

• RedstoneWill/HsuanTienLin_MachineLearning

  2.7k1035855

• chengtan9907/OpenSTL

  OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

  Language:Python8049153133

• IvanReznikov/DataVerse

  Public code of Dr. Ivan Reznikov used in posts, articles, conferences

  Language:Jupyter Notebook25215444

• danfenghong/IEEE_TGRS_SpectralFormer

  Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Spectralformer: Rethinking hyperspectral image classification with transformers, IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2021

  Language:Python23462738

• mys007/ecc

  Edge-Conditioned Convolutions on Graphs

  Language:Python23012948

• danfenghong/IEEE_TPAMI_SpectralGPT

  Hong, D., Zhang, B., Li, X., Li, Y., Li, C., Yao, J., Yokoya, N., Li, H., Ghamisi, P., Jia, X., Plaza, A. and Gamba, P., Benediktsson, J., Chanussot, J. (2024). SpectralGPT: Spectral remote sensing foundation model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024. DOI:10.1109/TPAMI.2024.3362475.

  Language:Python19552722

• carbonplan/cmip6-downscaling

  Climate downscaling using CMIP6 data

  Language:Jupyter Notebook179134727

• nasa/EMIT-Data-Resources

  This repository provides guides, short how-tos, and tutorials to help users access and work with data from the Earth Surface Mineral Dust Source Investigation (EMIT) mission.

  Language:HTML147152083

• Envirometrix/PredictiveSoilMapping

  Predictive Soil Mapping with R (book)

  Language:TeX8916742

• carlos-gg/dl4ds

  Deep Learning for empirical DownScaling. Python package with state-of-the-art and novel deep learning algorithms for empirical/statistical downscaling of gridded data

  Language:Jupyter Notebook8531027

• takh04/QCNN

  Language:Python783337

• Aalto-QuML/ClimODE

  ClimODE: Climate and Weather Forecasting With Physics-informed Neural ODEs

  Language:Python74079

• mrke/NicheMapR

  R implementation of Niche Mapper software for biophysical modelling

  Language:R66172334

• dengweihuan/SSDGL

  SSDGL: A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification (TCYB2021) https://ieeexplore.ieee.org/document/9440852

  Language:Python522715

• efluet/wetloss

  R scripts mapping global wetland loss (1700-2000)

  Language:R17203

• oreopie/physics-aware-dl

  Keras implementation for our paper "Improving AI system awareness of geoscience knowledge"

  Language:Jupyter Notebook14206

• CARDAMOM-framework/CARDAMOM_v2.2

  Language:C11606

• ASUcicilab/explainable-geoai

  Language:Python10300

• YanlanLiu/model-data-fusion

  Language:Python7202

• louisXW/PODS

  An optimization toolbox for computing expensive environmental models

  Language:Python6111

• KailiangYu/Biogeography-of-soil-microbes

  Language:JavaScript4101

• xmblb/HeterogeneousEnsemble

  data for IJGIS

  Language:Python4104

• lyang19/cluster-splmm

  Language:R2111

• geogismx/EMIT-Data-Resources

  This repository provides guides, short how-tos, and tutorials to help users access and work with data from the Earth Surface Mineral Dust Source Investigation (EMIT) mission.

  Language:HTML1000

• geogismx/heatnet

  Language:Python1000

• geogismx/ProfoundData

  Checking and benchmarking of dynamic vegetation models

  Language:HTML1000

• iREACH-UBC/PLUME_Dashboard

  Data visualization dashboard with post processing features designed specifically for mobile air quality monitoring

  Language:Python11