Alternatives and similar repositories for fenchel-young-losses

Users that are interested in fenchel-young-losses are comparing it to the libraries listed below

• 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
• leonardblier / alrao
  Implementation of "Learning with Random Learning Rates" in PyTorch.
  ☆102Updated 5 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 6 years ago
• akosiorek / forge
  Basic experiment framework for tensorflow.
  ☆91Updated 4 years ago
• MaestroGraph / sparse-hyper
  Code for the paper "Learning sparse transformations through backpropagation"
  ☆43Updated 5 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 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 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• golkar / backdrop
  Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.
  ☆68Updated 7 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• ermongroup / BiasAndGeneralization
  ☆27Updated 6 years ago
• viking-sudo-rm / stacknn-core
  Pip-installable differentiable stacks in PyTorch!
  ☆65Updated 5 years ago
• jpeg729 / pytorch_bits
  ☆80Updated 7 years ago
• hal3 / macarico
  learning to search in pytorch
  ☆110Updated 5 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 6 years ago
• edwardlib / observations
  Tools for loading standard data sets in machine learning
  ☆204Updated 2 years ago
• ajbrock / BoilerPlate
  Odds and Ends and Things I've implemented.
  ☆78Updated 6 years ago
• BorealisAI / lite_tracer
  a light weight experiment reproducibility toolset
  ☆40Updated 5 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆48Updated 7 years ago
• kyunghyuncho / backprop-kalman-filter
  ☆45Updated 5 years ago
• noahgolmant / skeletor
  A tiny module for machine learning experiment orchestration
  ☆63Updated 6 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 2 years ago
• Orcuslc / OrthNet
  TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials
  ☆31Updated 7 years ago
• inferno-pytorch / speedrun
  Research code need not be ugly.
  ☆77Updated 2 years ago
• viking-sudo-rm / StackNN
  Experiments with differentiable stacks and queues in PyTorch
  ☆144Updated 6 years ago
• yaringal / acquisition_example
  Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function
  ☆16Updated 8 years ago
• tfrerix / proxprop
  Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
  ☆42Updated 6 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago