Repository for UAI 2021 paper "Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fail at Reliable OOD Detection".
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Updated
Feb 3, 2022 - Jupyter Notebook
Repository for UAI 2021 paper "Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fail at Reliable OOD Detection".
This analysis refers to uncertainity, both model uncertainity and data uncertainity.
Its is an End-to-End Random forest implementation includes data preprocessing [ cleaning, feature selection and engineering],EDA, hyperparameter tuning, Model interpretation with uncertainty and prediction intervals and plotting the feature importance .
From Registration Uncertainty to Segmentation Uncertainty (ISBI 2024)
Bayesian neural networks in PyTorch
Numeric estimation of statistical uncertainties for Bernoulli experiments (k/n successful trials)
Tracking an embodied AI agent to estimate movement from observations
Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR2021).
Simple dead reckoning example in one dimension
MUBen: Benchmarking the Uncertainty of Molecular Representation Models
The source code for the Layer Ensembles paper published in MICCAI 2022 (Singapore).
Code for paper Multiomics dynamic learning enables personalized diagnosis and prognosis for pan-cancer and cancer-subtypes
Reproducible experiments conducted in the paper 'Uncertainty Quantification in Anomaly Detection with Cross-Conformal p-Values'.
The implementations for SLURP: Side Learning Uncertainty for Regression Problems (BMVC 2021)
Conformal Predictions using photonai
An unofficial PyTorch implementation of Self-supervised Depth Estimation from Spectral Consistency and Novel View Synthesis
This code performs generalized Brownian dynamics (GBD) simulations of a microparticle embedded in a viscoelastic fluid and calculates and propagates statistical and other sources of error in passive microrheology
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression [AAAI2024]
Monte Carlo Batch Normalization implementation in Pytorch
A python toolbox for uncertainty quantification, robustness assessment, and calibration metrics, methods and techniques in Deep Learning
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