Alternatives and similar repositories for StochasticMirrorDescent

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

• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• benchopt / benchmark_bilevel
  Benchmark for bi-level optimization solvers
  ☆44Updated 5 months ago
• daniellevy / fast-dro
  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
  ☆60Updated 2 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• umutsimsekli / sgd_tail_index
  The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"
  ☆25Updated 5 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated 2 months ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated 10 months ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆90Updated 3 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆146Updated 11 months ago
• gknilsen / pyhessian
  pyhessian is a TensorFlow module which can be used to estimate Hessian matrices
  ☆24Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆44Updated last year
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆111Updated 5 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆84Updated 4 years ago
• damaru2 / ntk
  NTK reading group
  ☆88Updated 5 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆66Updated 6 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 9 months ago
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆60Updated 6 years ago
• avirmaux / lipEstimation
  ☆58Updated 2 years ago
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆47Updated 3 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• arobey1 / LipSDP
  LipSDP - Lipschitz Estimation for Neural Networks
  ☆67Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆65Updated last month