Alternatives and similar repositories for Randomized_SVD_GPU

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

• kilianFatras / variance_reduced_neural_networks
  Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
  ☆74Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆49Updated 4 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• WenboGong / MetaSGMCMC
  The code for Meta Learning for SGMCMC
  ☆25Updated 6 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 8 months ago
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆44Updated 6 years ago
• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 5 years ago
• amirgholami / HessianFlow
  ☆83Updated 5 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆48Updated 2 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆49Updated 5 years ago
• cybertronai / pytorch-sso
  PyTorch-SSO: Scalable Second-Order methods in PyTorch
  ☆148Updated 2 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆147Updated last year
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 6 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• QUVA-Lab / COMBO
  ☆50Updated last year
• massastrello / awesome-implicit-neural-models
  ☆105Updated 4 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆130Updated 5 years ago
• mariogeiger / hessian
  hessian in pytorch
  ☆187Updated 5 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• akshayka / hessian_trace_estimation
  Hessian trace estimation using PyTorch and Hutch++
  ☆20Updated 5 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆21Updated 2 years ago
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆60Updated 7 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆77Updated last year
• pfnet-research / einconv
  ☆47Updated 6 years ago
• sphinxteam / dnner
  Deep Neural Networks Entropy from Replicas
  ☆34Updated 6 years ago