Alternatives and similar repositories for adaptive_GD:

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

• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated last month
• moskomule / hypergrad
  Simple and extensible hypergradient for PyTorch
  ☆16Updated 2 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆75Updated 6 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆20Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 8 months ago
• minhtannguyen / SRSGD
  Code base for SRSGD.
  ☆28Updated 5 years ago
• gpeyre / 2021-NonCvxPro
  ☆11Updated 3 years ago
• jshe / wasserstein-2
  ☆13Updated 6 years ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆39Updated 4 years ago
• thegregyang / NTK4A
  Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"
  ☆106Updated 4 years ago
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆131Updated 5 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• smortezavi / Randomized_SVD_GPU
  Attempt to speed Randomized SVD(Singular Value Decomposition) Using pytorch and it's gnu capabilities.
  ☆17Updated 6 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆66Updated 6 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆74Updated 8 months ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• dair-iitd / dl-with-constraints
  Code for experiments in 'Primal Dual Formulation For Deep Learning With Constraints'
  ☆22Updated 5 years ago
• gd-zhang / Follow-the-Ridge
  Minimax Optimization, Stackelberg Games, Generative Adversarial Networks
  ☆19Updated 5 years ago
• kazukiosawa / ngd_in_wide_nn
  simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…
  ☆14Updated 4 years ago
• f-t-s / CGD
  This repository contains the Julia code for the paper "Competitive Gradient Descent"
  ☆24Updated 5 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆20Updated 6 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• gkdziugaite / pacbayes-opt
  Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights
  ☆27Updated 4 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago