Alternatives and similar repositories for Randomly-Pivoted-Cholesky

Users that are interested in Randomly-Pivoted-Cholesky are comparing it to the libraries listed below

• mbilos / stribor
  Library for normalizing flows and neural flows.
  ☆26Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆65Updated last year
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 8 months ago
• modichirag / GSM-VI
  Code for Gaussian Score Matching Variational Inference
  ☆35Updated 10 months ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 4 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆85Updated 2 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆78Updated 4 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆120Updated last week
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆55Updated 4 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆41Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆153Updated 3 weeks ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆23Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• pierreablin / ksddescent
  Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities
  ☆22Updated last year
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆40Updated 3 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆51Updated 4 months ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated 2 years ago
• gaoliyao / Replica_Exchange_Stochastic_Gradient_MCMC
  Code for Non-convex Learning via Replica Exchange Stochastic Gradient MCMC, ICML 2020.
  ☆26Updated 5 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆53Updated 2 years ago