wiseodd / last_layer_laplace

Related projects: ⓘ

• rpinsler / active-bayesian-coresets
  ☆38Updated 4 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated last year
• KaosEngineer / PriorNetworks
  ☆65Updated 4 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆36Updated 3 years ago
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆34Updated 2 years ago
• IntelLabs / AVUC
  Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
  ☆51Updated last year
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆39Updated 10 months ago
• nikitadurasov / masksembles
  Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
  ☆98Updated 7 months ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆59Updated 3 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 3 years ago
• JanRocketMan / regression-prior-networks
  An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.
  ☆35Updated 3 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆39Updated last year
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆81Updated 4 months ago
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆38Updated last year
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆33Updated 5 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆109Updated 2 years ago
• facebookresearch / jacobian_regularizer
  A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.
  ☆124Updated last year
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆72Updated 11 months ago
• RylanSchaeffer / HarvardAM207-prior-networks
  Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks
  ☆12Updated 4 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆94Updated last year
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆149Updated 8 months ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆33Updated 3 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆43Updated 3 years ago
• uu-sml / calibration
  Python package for evaluating model calibration in classification
  ☆19Updated 4 years ago
• RAIVNLab / supsup
  Code for "Supermasks in Superposition"
  ☆115Updated 11 months ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆121Updated last year
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 3 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 3 years ago
• EvZissel / Residual-Flow
  An implementation of the Residual Flow algorithm for out-of-distribution detection.
  ☆29Updated 2 years ago
• preetum / cifar5m
  CIFAR-5m dataset
  ☆39Updated 3 years ago