Alternatives and similar repositories for Cubist

Users that are interested in Cubist are comparing it to the libraries listed below

• jasperroebroek / sklearn-quantile
  ☆23Updated 6 months ago
• WentaoZhan1998 / geospaNN
  ☆14Updated 4 months ago
• sustainability-lab / polire
  Spatial Interpolation in Python
  ☆13Updated last year
• kikocorreoso / scikit-extremes
  scikit-extremes is a basic statistical package to perform univariate extreme value calculations using Python
  ☆42Updated 3 years ago
• daleroberts / hdmedians
  High-dimensional medians (medoid, geometric median, etc.). Fast implementations in Python.
  ☆77Updated last year
• PySloth / pysloth
  A Python Package for Probabilistic Prediction
  ☆22Updated 4 years ago
• konstantinklemmer / sxl
  SXL: Spatially explicit learning of geographic processes with auxiliary tasks
  ☆15Updated 3 years ago
• ml-clim / drought-prediction
  A Machine Learning Pipeline to Predict Vegetation Health
  ☆31Updated 5 years ago
• nci / scores
  scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
  ☆184Updated last week
• OpheliaMiralles / pykelihood
  package useful for likelihood-based inference
  ☆13Updated this week
• fonnesbeck / probabilistic_python
  PyData London 2022 Tutorial
  ☆67Updated 3 years ago
• pyronear / pyro-risks
  Data science for wildfire risk forecasting and monitoring
  ☆26Updated last year
• SamComber / spacv
  Spatial cross-validation in Python.
  ☆47Updated last year
• mjhajharia / pydata21
  Pydata talk - Football Analytics Using Hierarchical Bayesian Models in PyMC
  ☆26Updated 3 years ago
• felipeangelimvieira / prophetverse
  A multiverse of Prophet models for timeseries
  ☆66Updated last week
• jnelson18 / pyquantrf
  Here is a [quantile random forest](http://jmlr.org/papers/v7/meinshausen06a.html) implementation that utilizes the [SciKitLearn](https://…
  ☆18Updated 9 months ago
• raybellwaves / xskillscore-tutorial
  ☆10Updated 4 years ago
• jmframe / mclstm_2021_extrapolate
  Code and models for the HESS paper on mass conservation and extrapolation with deep learning
  ☆14Updated 2 years ago
• frazane / scoringrules
  Lightweight library for probabilistic forecast evaluation and optimization.
  ☆63Updated 2 weeks ago
• jgomezdans / gp_emulator
  Gaussian Process emulators in Python
  ☆18Updated 6 years ago
• openclimatefix / satflow
  Satellite Optical Flow with machine learning models
  ☆62Updated last year
• monte-flora / scikit-explain
  A user-friendly python package for computing and plotting machine learning explainability output.
  ☆39Updated last year
• properscoring / properscoring
  Proper scoring rules in Python
  ☆178Updated 2 years ago
• FK83 / scoringRules
  scoring rules to evaluate probabilistic forecasts
  ☆63Updated last year
• charliekirkwood / deepgeostat
  Code for the paper - "Bayesian deep learning for spatial interpolation in the presence of auxiliary information"
  ☆27Updated 3 years ago
• AtrCheema / SeqMetrics
  Various errors for tabular/structured/time-series data
  ☆17Updated 7 months ago
• JohnGoertz / Gumbi
  Gaussian Process Model Building Interface
  ☆51Updated 6 months ago
• saattrupdan / doubt
  Bringing back uncertainty to machine learning.
  ☆53Updated last year
• pgbrodrick / ecoCNN
  A CNN for remotely sensed imagery, with emphasis on the IO pipeline to construct and apply the model.
  ☆25Updated 4 years ago
• USDA-ARS-NWRC / topocalc
  Sky view and terrain configuration factors
  ☆17Updated 3 months ago