Alternatives and similar repositories for RegularizedNonlinearAcceleration

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

• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆82Updated 7 years ago
• mariogeiger / hessian
  hessian in pytorch
  ☆187Updated 4 years ago
• ermongroup / a-nice-mc
  Code for "A-NICE-MC: Adversarial Training for MCMC"
  ☆126Updated 7 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• fKunstner / fast-individual-gradients-with-autodiff
  ☆26Updated 6 years ago
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆48Updated 7 months ago
• tfrerix / proxprop
  Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
  ☆42Updated 6 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• mstaib / stochastic-barycenter-code
  Supporting code for "Parallel Streaming Wasserstein Barycenters"
  ☆10Updated 7 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 6 years ago
• vsyrgkanis / optimistic_GAN_training
  ☆46Updated 7 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆46Updated 9 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 11 months ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 5 years ago
• gdebie / stochastic-deep-networks
  Stochastic Deep Networks
  ☆17Updated 6 years ago
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆130Updated 5 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• toiaydcdyywlhzvlob / backpack
  This repository is no longer maintained. Check
  ☆81Updated 5 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆149Updated last year
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆61Updated 7 years ago