Alternatives and similar repositories for Symbolic-Metamodeling

Users that are interested in Symbolic-Metamodeling are comparing it to the libraries listed below

• rgiordan / vittles
  "Variational inference tools to leverage estimator sensitivity."
  ☆16Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• JonathanCrabbe / Symbolic-Pursuit
  Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"
  ☆15Updated 2 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆49Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• kazukiosawa / ngd_in_wide_nn
  simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…
  ☆14Updated 4 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 4 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆77Updated last year
• darrenjw / logreg
  Bayesian inference for a logistic regression model in various languages
  ☆42Updated 2 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆22Updated 4 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆35Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• neildhir / DCBO
  Dynamic causal Bayesian optimisation
  ☆39Updated 2 years ago
• QUVA-Lab / COMBO
  ☆51Updated 11 months ago
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆49Updated 3 years ago
• probml / bandits
  Bayesian Bandits
  ☆68Updated last year
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆85Updated last year
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆121Updated 3 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆32Updated 6 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 11 months ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 5 years ago
• probml / JSL
  Jax SSM Library
  ☆49Updated 2 years ago
• mlysy / rodeo-legacy
  Probabilistic Solution of Differential Equations
  ☆13Updated 3 years ago