Alternatives and similar repositories for deep_learning_theory_tutorial

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

• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 5 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• jinglingli / nn-extrapolate
  ☆13Updated 3 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆47Updated 2 years ago
• rgrosse / csc2541_examples
  ☆30Updated 4 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• automl / nes
  Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
  ☆33Updated last week
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆96Updated 3 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago
• yilundu / improved_contrastive_divergence
  [ICML'21] Improved Contrastive Divergence Training of Energy Based Models
  ☆69Updated 3 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 6 years ago
• gibipara92 / learning-explanations-hard-to-vary
  Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …
  ☆41Updated 5 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆68Updated 6 years ago
• modestyachts / neural_kernels_code
  ☆35Updated 4 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• brandontrabucco / design-baselines
  Baselines for Model-Based Optimization
  ☆55Updated 3 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 3 years ago
• ayulockin / LossLandscape
  Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …
  ☆66Updated 5 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 5 years ago
• GAMES-UChile / The_Art_of_Gaussian_Processes
  ☆40Updated last month
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆112Updated 6 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆46Updated 3 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 4 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago