Alternatives and similar repositories for sklearn-hogwild

Users that are interested in sklearn-hogwild are comparing it to the libraries listed below

• isl-org / LMRS
  Source code for ICLR 2020 paper: "Learning to Guide Random Search"
  ☆40Updated 10 months ago
• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆82Updated 7 years ago
• sarlinpe / Concrete-Dropout
  A clean TensorFlow implementation of Concrete Dropout
  ☆22Updated 7 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 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
• ravidziv / Information-bottleneck
  Python implementation of the infomration bottleneck method (tishby et al, 1999)
  ☆36Updated 8 years ago
• xbresson / IPAM_Tutorial_2019
  Notebooks for IPAM Tutorial, March 15 2019
  ☆24Updated 6 years ago
• brain-research / conv-sv
  The Singular Values of Convolutional Layers
  ☆72Updated 6 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆45Updated 6 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• eBay / AutoOpt
  Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent
  ☆45Updated 4 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 5 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• ron-amit / meta-learning-adjusting-priors2
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆18Updated 4 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 5 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• davidstutz / cvpr2019-adversarial-robustness
  CVPR 2019 paper "Disentangling Adversarial Robustness and Generalization".
  ☆14Updated 5 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• ermongroup / f-wgan
  Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020
  ☆14Updated 5 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• kilianFatras / variance_reduced_neural_networks
  Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
  ☆72Updated 4 years ago
• yosinski / GitResultsManager
  A simple snapshotting system for managing research results using Git.
  ☆30Updated 3 months ago
• lorraine2 / hypernet-hypertraining
  Code for Stochastic Hyperparameter Optimization through Hypernetworks
  ☆23Updated 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 5 years ago
• mlresearch / v97
  Proceedings of ICML 2019
  ☆33Updated 2 years ago
• KordingLab / hilbert-constrained-gradient-descent
  Pytorch optimizers implementing Hilbert Constrained Gradient Descent
  ☆19Updated 6 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 6 years ago
• Justin-Tan / entropy-sgd-tf
  TensorFlow implementation of entropy SGD
  ☆11Updated 6 years ago