Alternatives and similar repositories for phd-thesis

Users that are interested in phd-thesis are comparing it to the libraries listed below

• f-dangel / vivit
  [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…
  ☆17Updated last year
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• probabilistic-numerics / probnum-spring-school
  Tutorial materials of the Probabilistic Numerics Spring School.
  ☆34Updated 2 years ago
• RussellTsuchida / snefy
  An implementation of squared neural families in PyTorch
  ☆14Updated 8 months ago
• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆40Updated 2 months ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• wesselb / lab
  A generic interface for linear algebra backends
  ☆73Updated 4 months ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆104Updated last year
• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆43Updated last year
• pierreablin / ksddescent
  Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities
  ☆21Updated last year
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆49Updated last year
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• egstatsml / arxivsearch
  Pulls papers from arXiv on a weekly basis
  ☆30Updated last year
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 4 years ago
• wesselb / NeuralProcesses.jl
  A framework for composing Neural Processes in Julia
  ☆76Updated 4 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• AaltoML / PeriodicBNN
  Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)
  ☆19Updated 3 years ago
• aboustati / vargrad
  Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference
  ☆12Updated 4 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆67Updated 2 months ago
• mathurinm / andersoncd
  This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only ser…
  ☆18Updated 2 years ago
• glouppe / flowing-with-jax
  ☆15Updated 4 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago