Alternatives and similar repositories for metropolis_hastings_from_scratch

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

• se-jaeger / conformal-data-cleaning
  Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…
  ☆24Updated last year
• vacquaviva / IntroConformalPredictions
  A short introduction to Conformal Prediction methods, with a few examples for classification and regression from the Astrophysical domain…
  ☆12Updated last year
• fonnesbeck / probabilistic_python
  PyData London 2022 Tutorial
  ☆67Updated 3 years ago
• vincentblot28 / conformalized_gp
  ☆48Updated 7 months ago
• rasbt / scipy2022-talk
  ☆26Updated 3 years ago
• PySloth / pysloth
  A Python Package for Probabilistic Prediction
  ☆22Updated 4 years ago
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆49Updated 3 years ago
• flyteorg / flyte-conference-talks
  A repo of Flyte-related conference talks
  ☆14Updated last year
• sidhu2690 / Deep-KAN
  This repository contains a better implementation of Kolmogorov-Arnold networks
  ☆63Updated 3 months ago
• nmdwolf / ValidPredictionIntervals
  Contains the code to run the different models considered in the paper "Valid prediction intervals for regression problems"
  ☆19Updated 2 years ago
• ogrisel / euroscipy-2022-time-series
  Tutorial on time-series forcasting with scikit-learn
  ☆33Updated 2 years ago
• ronikobrosly / scipy_2023_causal_inference_tutorial
  Materials for a proposed Causal Inference Tutorial session at SciPy 2023
  ☆12Updated 2 years ago
• varsha2509 / hyperlocal-aq-prediction
  ☆21Updated last year
• microprediction / timeseries-elo-ratings
  Elo ratings for time-series forecasting packages
  ☆24Updated 3 years ago
• Carl-McBride-Ellis / TOBoML
  The Orange Book of Machine Learning
  ☆47Updated 5 months ago
• lrjball / shap
  A game theoretic approach to explain the output of any machine learning model.
  ☆14Updated 3 years ago
• ChrisD-7 / Fraud-Detection-in-Supply-Chains-with-Kolmogorov-Arnold-Networks
  An attempt to use KAN
  ☆12Updated last year
• tblume1992 / MFLES
  ☆115Updated last year
• tcapelle / torch_moving_mnist
  A simple Dataset generator for Moving Mnist
  ☆13Updated 2 years ago
• GeostatsGuy / GeostatsPyDemos
  Well-documented demonstration workflows with the GeostatsPy package.
  ☆56Updated last year
• JesperDramsch / ml.recipes
  Increase citations, ease review & collaboration A collection of "easy wins" to make machine learning in research reproducible. This tut…
  ☆74Updated 3 weeks ago
• donlapark / coverforest
  A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.
  ☆44Updated 3 weeks ago
• ran-xie / boosted-conformal
  ☆39Updated 8 months ago
• koaning / scikit-mdn
  A mixture density network, by PyTorch, for scikit-learn
  ☆23Updated 9 months ago
• AlexIoannides / llm-regression
  Exploring the classical regression capabilities of LLMs.
  ☆18Updated last year
• thomasjpfan / ml-workshop-advanced
  ☆15Updated 3 years ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆70Updated last week
• AllenDowney / BayesianInferencePyMC
  Workshop on Bayesian inference using PyMC
  ☆27Updated 4 years ago
• tee-lab / PyDaddy
  Python package to discover stochastic differential equations from time series data
  ☆96Updated 7 months ago
• millengustavo / time-series-forecasting
  Notes on time series forecasting
  ☆15Updated 5 years ago