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Uncertainty Quantification

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/arplaboratory/UASTHN

공식 코드

UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization

https://github.com/asaoulis/seismo-sbi

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Full-waveform earthquake source inversion using simulation-based inference

https://github.com/asonabend/ESRL

공식 코드

Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation

https://github.com/ast-fortiss-tum/misbehaviour-prediction-with-uncertainty-quantification

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Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification

https://github.com/astro-informatics/quantifai

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Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging

https://github.com/aterenin/geometric_asymptotics

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Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds

https://github.com/athulrs177/forecast_models

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Machine learning models for daily rainfall forecasting in Northern Tropical Africa using tropical wave predictors

https://github.com/audeering/ser-uncertainty-quantification

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Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion Recognition

https://github.com/autonomousvision/akorn

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Artificial Kuramoto Oscillatory Neurons

https://github.com/avakanski/Fatigue-Life-Prediction

공식 코드

Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning

https://github.com/avakanski/creep-uncertainty-quantification

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Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks

https://github.com/averysi224/pac-ps-label-shift

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PAC Prediction Sets Under Label Shift

https://github.com/awakermhy/mnn_wm_uq

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Uncertainty Quantification in Working Memory via Moment Neural Networks

https://github.com/awakermhy/probabilistic-computing-mnn

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Probabilistic computation and uncertainty quantification with emerging covariance

https://github.com/awslabs/fortuna

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Fortuna: A Library for Uncertainty Quantification in Deep Learning

https://github.com/azizanlab/repreli

공식 코드

Quantifying Representation Reliability in Self-Supervised Learning Models

https://github.com/b-remy/score-estimation-comparison

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Denoising Score-Matching for Uncertainty Quantification in Inverse Problems

https://github.com/baichenjia/pbrl

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Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

https://github.com/baichenjia/utds

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Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning

https://github.com/bccp/DeepUQ

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Uncertainty Quantification with Generative Models

https://github.com/bdevl/PGMCPC

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A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables

https://github.com/beneboeck/sparse-bayesian-gen-mod

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Sparse Bayesian Generative Modeling for Compressive Sensing

https://github.com/benmltu/scalarize

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Random Pareto front surfaces

https://github.com/benolmbrt/wcp_miccai

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Robust Conformal Volume Estimation in 3D Medical Images

https://github.com/berkeleyautomation/iifl

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IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors

https://github.com/bessagroup/mfbml

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Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models

https://github.com/bezirganyan/DBF_uncertainty

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Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion

https://github.com/bezirganyan/luma

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LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal Data

https://github.com/bhaweshiitk/conformalllm

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Conformal Prediction with Large Language Models for Multi-Choice Question Answering

https://github.com/bhouri0412/hist_bayesian_closure

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History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96

https://github.com/bmucsanyi/bud

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Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks

https://github.com/bmucsanyi/untangle

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Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks

https://github.com/bobby-he/uncertainr

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UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography

https://github.com/bonstats/bayesscorecal.jl

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Bayesian score calibration for approximate models

https://github.com/boschresearch/ube-mbrl

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Model-Based Uncertainty in Value Functions

https://github.com/bu-cisl/illumination-coding-meets-uncertainty-learning

공식 코드

Reliable deep-learning-based phase imaging with uncertainty quantification

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