Alternatives and similar repositories for tf_optimizers:

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

• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 5 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• MaestroGraph / sparse-hyper
  Code for the paper "Learning sparse transformations through backpropagation"
  ☆43Updated 5 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆41Updated 6 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 7 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 7 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆53Updated 5 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated last year
• kimhc6028 / pathnet-pytorch
  PyTorch implementation of PathNet: Evolution Channels Gradient Descent in Super Neural Networks
  ☆80Updated 7 years ago
• lballes / msvag
  TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.
  ☆44Updated 6 years ago
• Shallow-Updates-for-Deep-RL / Shallow_Updates_for_Deep_RL
  Official implementation for the paper: "Shallow Updates for Deep Reinforcement Learning"
  ☆18Updated 7 years ago
• ron-amit / meta-learning-adjusting-priors
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆22Updated 5 years ago
• artix41 / AVO-pytorch
  Implementation of Adversarial Variational Optimization in PyTorch
  ☆43Updated 6 years ago
• BB-UCL / Lasagne
  ☆13Updated 6 years ago
• rizar / systematic-generalization-sqoop
  Code for "Systematic Generalization: What Is Required and Can It Be Learned"
  ☆37Updated 5 years ago
• lorraine2 / hypernet-hypertraining
  Code for Stochastic Hyperparameter Optimization through Hypernetworks
  ☆23Updated 6 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆48Updated 5 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• wlwkgus / NoisyNaturalGradient
  Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"
  ☆121Updated 6 years ago
• myshkov / bnn-analysis
  ☆16Updated 8 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 5 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 years ago
• joelouismarino / amortized-variational-filtering
  PyTorch implementation of AVF
  ☆45Updated 4 years ago