Alternatives and similar repositories for ngd_in_wide_nn

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

• gehring / fax
  ☆80Updated 4 years ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆42Updated 5 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆88Updated 3 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 years ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆124Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆54Updated 5 years ago
• jonasrothfuss / meta_learning_pacoh
  Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds
  ☆26Updated last year
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• juliagusak / neural-ode-norm
  Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"
  ☆16Updated 5 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆86Updated 2 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 10 months ago
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆132Updated 6 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• jamesvuc / jax-bayes
  Bayesian inference with Python and Jax.
  ☆34Updated 3 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆39Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• cgarciae / treeo
  A small library for creating and manipulating custom JAX Pytree classes
  ☆56Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• QUVA-Lab / COMBO
  ☆50Updated last year