YoungseogChung / calibrated-quantile-uq

Related projects ⓘ

Alternatives and complementary repositories for calibrated-quantile-uq

• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆36Updated 2 years ago
• AnthonyRentsch / calibrated_regression
  A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.
  ☆50Updated 4 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated last year
• vistalab-technion / vqr
  Vector Quantile Regression
  ☆19Updated last year
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated 9 months ago
• networkslab / rnn_flow
  ☆22Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆86Updated 4 years ago
• kashif / uncertainty-metrics
  Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…
  ☆21Updated 4 years ago
• msesia / chr
  Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
  ☆20Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆27Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆66Updated 2 weeks ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆37Updated 8 months ago
• Srceh / DistCal
  Code for the ICML 2019 paper: Distribution Calibration for Regression
  ☆21Updated last year
• 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 2 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆64Updated this week
• Rose-STL-Lab / Spatiotemporal_UQ
  Uncertainty Quantification for Deep Spatiotemporal Forecasting
  ☆21Updated 2 months ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• MarkPKCollier / MissingDataVAEs
  ☆19Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 5 months ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆68Updated 4 years ago
• mrojascarulla / causal_transfer_learning
  ☆30Updated 6 years ago
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆41Updated 4 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆27Updated 3 years ago
• ahmedmalaa / discriminative-jackknife
  Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.
  ☆8Updated 4 years ago
• Junghwan-brian / SDE-Net
  implementations sde-net
  ☆14Updated 3 years ago
• sjblim / rmsn_nips_2018
  ☆37Updated 5 years ago