Alternatives and similar repositories for lula

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

• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated 2 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆36Updated 3 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆32Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 2 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆76Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated last month
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated last year
• JanRocketMan / regression-prior-networks
  An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.
  ☆36Updated 4 years ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated last year
• CalculatedContent / ww-trends-2020
  ☆18Updated 4 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆43Updated 7 months ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆85Updated last year
• xuwd11 / Dropout_Tutorial_in_PyTorch
  Dropout as Regularization and Bayesian Approximation
  ☆59Updated 6 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆22Updated 2 years ago
• mariushobbhahn / LB_for_BNNs_official
  Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. htt…
  ☆12Updated 3 years ago
• msesia / chr
  Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
  ☆22Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆37Updated last year
• AndrewAtanov / semi-supervised-flow-pytorch
  Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"
  ☆10Updated 5 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆82Updated 3 years ago
• JonathanCrabbe / Symbolic-Pursuit
  Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"
  ☆15Updated 2 years ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• jiaqima / SODEN
  SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
  ☆13Updated 2 years ago
• ganguli-lab / degrees-of-freedom
  ☆37Updated 3 years ago