Alternatives and similar repositories for AHGP:

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

• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 3 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 4 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆29Updated 3 years ago
• google-deepmind / annealed_flow_transport
  ☆49Updated last year
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆82Updated last year
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆44Updated 2 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆41Updated last year
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆11Updated last year
• AWehenkel / Graphical-Normalizing-Flows
  Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…
  ☆44Updated last year
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆24Updated last year
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆9Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆19Updated 6 months ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• vr308 / GPLVM
  Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
  ☆15Updated 3 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆27Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆38Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆32Updated 2 years ago