xinxxxin

xinxxxin's Stars

• adamlilith/fasterRaster_support

  Files for developers of the fasterRaster package

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• jupyterlab/jupyterlab

  JupyterLab computational environment.

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• pgbrodrick/ecoCNN

  A CNN for remotely sensed imagery, with emphasis on the IO pipeline to construct and apply the model.

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• jinyizju/V.PhyloMaker

  This R package makes phylogenetic hypotheses for a user-specified list of species at a faster speed than S.PhyloMaker

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• jinyizju/U.PhyloMaker

  This package aims to generate phylogenetic trees for a list of species of plants or animals, based on an existent backbone phylogeny.

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• Luisagi/enmpa

  Ecological Niche Modeling using Presence-Absence Data

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• wzmli/phyloglmm

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• xinxxxin/gdm

  R package for Generalized Dissimilarity Modeling. Compiled with R 4.0.2. Modified functions that work with 'sparseGDM' package.

  1

• xinxxxin/geneticOffsetR

  Custom R functions from: Fitzpatrick MC, Chhatre VE, Soolanayakanahally RY, Keller SR (in review) Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

  1

• xinxxxin/sgdm_package

  SGDM package. Compiled with R 4.0.2. Tested out internal functions from 'gdm' package.

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• BiogeographyLab/GridDER.github.io

  The package finds a grid system

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• fitzLab-AL/gdm

  R package for Generalized Dissimilarity Modeling

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• jeffheaton/t81_558_deep_learning

  T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

  Language:Jupyter Notebook5.7k3k

• tongqiugeog/mac_m1_deep_learning

  Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

  2

• daijiang/neonDivData

  Cleaned biodiversity data from NEON

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• r-lidar/lidR

  Airborne LiDAR data manipulation and visualisation for forestry application

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• mbjoseph/mnird

  (M)achine learning + (N)EON + (I)nstrumentation + literature (R)eview for + bio(D)iversity

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• danielegrattarola/spektral

  Graph Neural Networks with Keras and Tensorflow 2.

  Language:Python2.4k334

• FilippoMB/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling

  Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"

  Language:Python26048

• ritchieng/deep-learning-wizard

  Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, Apptainer, and more.

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• rmcelreath/stat_rethinking_2022

  Statistical Rethinking course winter 2022

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• sacridini/Awesome-Geospatial

  Long list of geospatial tools and resources

  4.1k623

• nsidc/earthaccess

  Python Library for NASA Earthdata APIs

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• 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.

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• vincenzocoia/Interpreting-Regression

  Notes for regression analysis, in the form of a bookdown book

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• helixcn/enmSdm

  Faster, better, smarter ecological niche modeling and species distribution modeling

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• helixcn/sdm_r_packages

  A curated list of R packages used in species distribution modelling

  4317