Alternatives and similar repositories for approxcdf

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

• jdb78 / lipo
  Global, derivative-free optimization for hyperparameter tuning
  ☆44Updated last month
• jessegrabowski / pymc_statespace
  A system for Bayesian estimation of state space models using PyMC
  ☆36Updated 4 months ago
• WenxinZhou / conquer
  Convolution Smoothed Quantile Regression
  ☆18Updated last year
• mattiasvillani / AdvBayesLearnCourse
  Course material for the PhD course in Advanced Bayesian Learning
  ☆59Updated 9 months ago
• bob-carpenter / adaptive-hmc
  Self-tuning HMC algorithms and evaluations
  ☆19Updated last year
• alisaab / l0bnb
  Solves the best subset selection problem
  ☆45Updated 3 years ago
• lanl / pyBASS
  Bayesian Adaptive Spline Surfaces for flexible and automatic regression
  ☆25Updated last month
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• tblume1992 / Seance
  Wrapper around MLForecast for more plug and play forecasting
  ☆10Updated 2 years ago
• martiningram / mcmc_runtime_comparison
  Compares Stan, PyMC, and PyMC + JAX numpyro sampler on a model for tennis
  ☆33Updated 2 years ago
• lee-group-cmu / RFCDE
  Random Forests for Conditional Density Estimation
  ☆43Updated 4 years ago
• jessegrabowski / statespace-presentation
  Presentation materials for PyMC Statespace
  ☆25Updated last year
• StatMixedML / DGBM
  Distributional Gradient Boosting Machines
  ☆27Updated 2 years ago
• JohnGoertz / Gumbi
  Gaussian Process Model Building Interface
  ☆51Updated 9 months ago
• probml / sts-jax
  Structural Time Series in JAX
  ☆210Updated last year
• flatironinstitute / bayes-kit
  Bayesian inference and posterior analysis for Python
  ☆46Updated last year
• lorismichel / drf
  Distributional Random Forests (Cevid et al., 2020)
  ☆45Updated this week
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 10 months ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆225Updated 11 months ago
• PrincetonLIPS / mf-bocd
  Active multi-fidelity Bayesian online changepoint detection.
  ☆18Updated 4 years ago
• pierrejacob / unbiasedmcmc
  Unbiased Markov chain Monte Carlo with couplings
  ☆30Updated 3 years ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆241Updated last year
• canyon289 / ssm_book_club
  ☆18Updated 2 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆45Updated 7 years ago
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 4 years ago
• blackjax-devs / sampling-book
  Tutorials and sampling algorithm comparisons
  ☆79Updated this week
• g-benton / Volt
  Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
  ☆49Updated 3 years ago
• yaronshap / GloballyConsistentRules
  Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…
  ☆25Updated 3 years ago
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆33Updated 2 years ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆120Updated 2 years ago