Alternatives and similar repositories for tf_optimizers

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

• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 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 7 years ago
• kimhc6028 / pathnet-pytorch
  PyTorch implementation of PathNet: Evolution Channels Gradient Descent in Super Neural Networks
  ☆81Updated 8 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 6 years ago
• akosiorek / forge
  Basic experiment framework for tensorflow.
  ☆91Updated 4 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated 2 years ago
• rizar / systematic-generalization-sqoop
  Code for "Systematic Generalization: What Is Required and Can It Be Learned"
  ☆37Updated 6 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆194Updated 2 years ago
• greentfrapp / cond-shift-neurons
  Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)
  ☆28Updated 7 years ago
• leonardblier / alrao
  Implementation of "Learning with Random Learning Rates" in PyTorch.
  ☆102Updated 6 years ago
• david-abel / icml_2019
  Notes for ICML 2019
  ☆38Updated 6 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 8 years ago
• Shallow-Updates-for-Deep-RL / Shallow_Updates_for_Deep_RL
  Official implementation for the paper: "Shallow Updates for Deep Reinforcement Learning"
  ☆18Updated 8 years ago
• MaestroGraph / sparse-hyper
  Code for the paper "Learning sparse transformations through backpropagation"
  ☆43Updated 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• artix41 / AVO-pytorch
  Implementation of Adversarial Variational Optimization in PyTorch
  ☆43Updated 7 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆76Updated 5 years ago
• goodfeli / forgetting
  Repository of code for the experiments for the ICLR submission "An Empirical Investigation of Catastrophic Forgetting in Gradient-Based N…
  ☆69Updated 11 years ago
• kyunghyuncho / backprop-kalman-filter
  ☆45Updated 6 years ago
• joelouismarino / amortized-variational-filtering
  PyTorch implementation of AVF
  ☆45Updated 5 years ago
• hal3 / macarico
  learning to search in pytorch
  ☆110Updated 5 years ago
• ermongroup / BiasAndGeneralization
  ☆28Updated 6 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 6 years ago
• lballes / msvag
  TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.
  ☆44Updated 7 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• vithursant / VAE-Gumbel-Softmax
  An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…
  ☆72Updated 7 years ago
• Cyanogenoid / perm-optim
  [ICLR 2019] Learning Representations of Sets through Optimized Permutations
  ☆36Updated 6 years ago
• amzn / metalearn-leap
  Original PyTorch implementation of the Leap meta-learner (https://arxiv.org/abs/1812.01054) along with code for running the Omniglot expe…
  ☆148Updated 2 years ago