Alternatives and similar repositories for laplace-refinement

Users that are interested in laplace-refinement are comparing it to the libraries listed below

• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆23Updated 5 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆17Updated last year
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• tijana-zrnic / active-inference
  ☆18Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• take-koshizuka / NLSB
  ☆21Updated 11 months ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated 7 months ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• necludov / action-matching
  Implementation of Action Matching for the Schrödinger equation
  ☆25Updated 2 years ago
• tung-nd / ExPT
  ☆18Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• Sulam-Group / k-rcps
  "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"
  ☆18Updated 3 weeks ago
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 4 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆41Updated 3 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆16Updated 4 years ago
• automl / PFNs4BO
  The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
  ☆38Updated 4 months ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆41Updated last year
• timgaripov / compositional-sculpting
  Code for paper "Compositional Sculpting of Iterative Generative Processes"
  ☆25Updated 2 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• FabianAltekrueger / NeuralWassersteinGradientFlows
  Implementation of the paper "Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels"
  ☆11Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• balintmate / boltzmann-interpolations
  ☆10Updated 2 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆12Updated 2 years ago
• cscarv / riemannian-metric-learning-ot
  ☆18Updated 2 years ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 3 years ago