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Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods

Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

21 October 2019
Eyke Hüllermeier
Willem Waegeman
    PER
    UD
ArXivPDFHTML

Papers citing "Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods"

50 / 550 papers shown
Title
Deal, or no deal (or who knows)? Forecasting Uncertainty in
  Conversations using Large Language Models
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models
Anthony Sicilia
Hyunwoo J. Kim
Khyathi Raghavi Chandu
Malihe Alikhani
Jack Hessel
18
1
0
05 Feb 2024
Deep autoregressive density nets vs neural ensembles for model-based
  offline reinforcement learning
Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning
Abdelhakim Benechehab
Albert Thomas
Balázs Kégl
OffRL
32
2
0
05 Feb 2024
EuroPED-NN: Uncertainty aware surrogate model
EuroPED-NN: Uncertainty aware surrogate model
A. P. Alvarez
A. Ho
A. Jarvinen
S. Saarelma
S. Wiesen
JET Contributors
13
0
0
01 Feb 2024
Linguistically Communicating Uncertainty in Patient-Facing Risk
  Prediction Models
Linguistically Communicating Uncertainty in Patient-Facing Risk Prediction Models
Adarsa Sivaprasad
Ehud Reiter
21
0
0
31 Jan 2024
Roq: Robust Query Optimization Based on a Risk-aware Learned Cost Model
Roq: Robust Query Optimization Based on a Risk-aware Learned Cost Model
Amin Kamali
Verena Kantere
C. Zuzarte
Vincent Corvinelli
30
0
0
26 Jan 2024
Reliability and Interpretability in Science and Deep Learning
Reliability and Interpretability in Science and Deep Learning
Luigi Scorzato
36
3
0
14 Jan 2024
Combining Confidence Elicitation and Sample-based Methods for
  Uncertainty Quantification in Misinformation Mitigation
Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation
Mauricio Rivera
Jean-François Godbout
Reihaneh Rabbany
Kellin Pelrine
HILM
21
9
0
13 Jan 2024
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware
  Adaptive Resource Oversubscription Policy
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy
Lu Wang
Mayukh Das
Fangkai Yang
Chao Duo
Bo Qiao
...
Chetan Bansal
Qingwei Lin
Saravan Rajmohan
Dongmei Zhang
Qi Zhang
113
0
0
13 Jan 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph
  Neural Networks
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi
Mark Heimann
Rushil Anirudh
Danai Koutra
Jayaraman J. Thiagarajan
UQCV
29
4
0
07 Jan 2024
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality,
  and a Future Outlook
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook
Mingyu Liu
Ekim Yurtsever
Jonathan Fossaert
Xingcheng Zhou
Walter Zimmer
Yuning Cui
B. L. Žagar
Alois C. Knoll
56
36
0
02 Jan 2024
Second-Order Uncertainty Quantification: Variance-Based Measures
Second-Order Uncertainty Quantification: Variance-Based Measures
Yusuf Sale
Paul Hofman
Lisa Wimmer
Eyke Hüllermeier
Thomas Nagler
PER
UQCV
UD
29
8
0
30 Dec 2023
Uncertainty Quantification in Machine Learning for Joint Speaker
  Diarization and Identification
Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification
Simon W. McKnight
Aidan O. T. Hogg
Vincent W. Neo
Patrick A. Naylor
11
1
0
28 Dec 2023
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty
  from Pre-trained Models
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
Gianni Franchi
Olivier Laurent
Maxence Leguéry
Andrei Bursuc
Andrea Pilzer
Angela Yao
UQCV
BDL
15
4
0
23 Dec 2023
Kernel Heterogeneity Improves Sparseness of Natural Images
  Representations
Kernel Heterogeneity Improves Sparseness of Natural Images Representations
Hugo J. Ladret
Christian Casanova
Laurent Udo Perrinet
17
0
0
22 Dec 2023
Auto311: A Confidence-guided Automated System for Non-emergency Calls
Auto311: A Confidence-guided Automated System for Non-emergency Calls
Zirong Chen
Xutong Sun
Yuanhe Li
Meiyi Ma
23
1
0
19 Dec 2023
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation
  in low-data regimes
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat
Nicolas Huynh
B. V. Breugel
M. Schaar
26
25
0
19 Dec 2023
Dirichlet-based Uncertainty Quantification for Personalized Federated
  Learning with Improved Posterior Networks
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks
Nikita Kotelevskii
Samuel Horváth
Karthik Nandakumar
Martin Takáč
Maxim Panov
UQCV
FedML
OOD
34
7
0
18 Dec 2023
Wiener Chaos in Kernel Regression: Towards Untangling Aleatoric and
  Epistemic Uncertainty
Wiener Chaos in Kernel Regression: Towards Untangling Aleatoric and Epistemic Uncertainty
T. Faulwasser
O. Molodchyk
33
1
0
12 Dec 2023
Consistency Models for Scalable and Fast Simulation-Based Inference
Consistency Models for Scalable and Fast Simulation-Based Inference
Marvin Schmitt
Valentin Pratz
Ullrich Kothe
Paul-Christian Bürkner
Stefan T. Radev
29
9
0
09 Dec 2023
Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with
  Denoising Diffusion Probabilistic Models
Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models
Qiang Liu
Nils Thuerey
DiffM
AI4CE
21
9
0
08 Dec 2023
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Philipp Reiser
Javier Enrique Aguilar
A. Guthke
Paul-Christian Bürkner
36
2
0
08 Dec 2023
Second-Order Uncertainty Quantification: A Distance-Based Approach
Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale
Viktor Bengs
Michele Caprio
Eyke Hüllermeier
PER
UQCV
UD
27
18
0
02 Dec 2023
Adaptive Correspondence Scoring for Unsupervised Medical Image
  Registration
Adaptive Correspondence Scoring for Unsupervised Medical Image Registration
Xiaoran Zhang
J. Stendahl
Lawrence H. Staib
Albert J Sinusas
Alex Wong
James S. Duncan
OOD
31
2
0
01 Dec 2023
Adaptability of Computer Vision at the Tactical Edge: Addressing
  Environmental Uncertainty
Adaptability of Computer Vision at the Tactical Edge: Addressing Environmental Uncertainty
Hayden Moore
19
0
0
01 Dec 2023
Deployment of a Robust and Explainable Mortality Prediction Model: The
  COVID-19 Pandemic and Beyond
Deployment of a Robust and Explainable Mortality Prediction Model: The COVID-19 Pandemic and Beyond
Jacob R. Epifano
Stephen Glass
Ravichandran Ramachandran
Sharad Patel
A. Masino
Ghulam Rasool
18
0
0
28 Nov 2023
Continual Learning: Applications and the Road Forward
Continual Learning: Applications and the Road Forward
Eli Verwimp
Rahaf Aljundi
Shai Ben-David
Matthias Bethge
Andrea Cossu
...
J. Weijer
Bing Liu
Vincenzo Lomonaco
Tinne Tuytelaars
Gido M. van de Ven
CLL
43
44
0
20 Nov 2023
How False Data Affects Machine Learning Models in Electrochemistry?
How False Data Affects Machine Learning Models in Electrochemistry?
Krittapong Deshsorn
L. Lawtrakul
Pawin Iamprasertkun
19
4
0
17 Nov 2023
Model Agnostic Explainable Selective Regression via Uncertainty
  Estimation
Model Agnostic Explainable Selective Regression via Uncertainty Estimation
Andrea Pugnana
Carlos Mougan
Dan Saattrup Nielsen
35
0
0
15 Nov 2023
Uncertainty Quantification in Machine Learning for Biosignal
  Applications -- A Review
Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review
Ivo Pascal de Jong
A. Sburlea
Matias Valdenegro-Toro
24
1
0
15 Nov 2023
Confident Naturalness Explanation (CNE): A Framework to Explain and
  Assess Patterns Forming Naturalness
Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness
Ahmed Emam
Mohamed Farag
R. Roscher
26
1
0
15 Nov 2023
Human-in-the-loop: Towards Label Embeddings for Measuring Classification
  Difficulty
Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty
Katharina Hechinger
Christoph Koller
Xiao Xiang Zhu
Goran Kauermann
UQCV
33
1
0
15 Nov 2023
Decomposing Uncertainty for Large Language Models through Input
  Clarification Ensembling
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou
Yujian Liu
Kaizhi Qian
Jacob Andreas
Shiyu Chang
Yang Zhang
UD
UQCV
PER
26
48
0
15 Nov 2023
Total Empiricism: Learning from Data
Total Empiricism: Learning from Data
Orestis Loukas
Holly Chung
27
3
0
14 Nov 2023
Introducing an Improved Information-Theoretic Measure of Predictive
  Uncertainty
Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty
Kajetan Schweighofer
L. Aichberger
Mykyta Ielanskyi
Sepp Hochreiter
23
11
0
14 Nov 2023
Uncertainty quantification and out-of-distribution detection using
  surjective normalizing flows
Uncertainty quantification and out-of-distribution detection using surjective normalizing flows
Simon Dirmeier
Ye Hong
Yanan Xin
Fernando Pérez-Cruz
UQCV
28
1
0
01 Nov 2023
Model Uncertainty based Active Learning on Tabular Data using Boosted
  Trees
Model Uncertainty based Active Learning on Tabular Data using Boosted Trees
Sharath M Shankaranarayana
29
0
0
30 Oct 2023
NPCL: Neural Processes for Uncertainty-Aware Continual Learning
NPCL: Neural Processes for Uncertainty-Aware Continual Learning
Saurav Jha
Dong Gong
He Zhao
Lina Yao
CLL
BDL
31
12
0
30 Oct 2023
Agreeing to Stop: Reliable Latency-Adaptive Decision Making via
  Ensembles of Spiking Neural Networks
Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks
Jiechen Chen
Sangwoo Park
Osvaldo Simeone
27
4
0
25 Oct 2023
Knowledge from Uncertainty in Evidential Deep Learning
Knowledge from Uncertainty in Evidential Deep Learning
Cai Davies
Marc Roig Vilamala
Alun D. Preece
Federico Cerutti
Lance M. Kaplan
Supriyo Chakraborty
EDL
16
2
0
19 Oct 2023
On the Temperature of Bayesian Graph Neural Networks for Conformal
  Prediction
On the Temperature of Bayesian Graph Neural Networks for Conformal Prediction
Seohyeon Cha
Honggu Kang
Joonhyuk Kang
20
3
0
17 Oct 2023
Certainty In, Certainty Out: REVQCs for Quantum Machine Learning
Certainty In, Certainty Out: REVQCs for Quantum Machine Learning
Hannah Helgesen
Michael Felsberg
Jan-AAke Larsson
27
0
0
16 Oct 2023
Uncertainty Quantification using Generative Approach
Uncertainty Quantification using Generative Approach
Yunsheng Zhang
UQCV
BDL
11
0
0
13 Oct 2023
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
Olivier Laurent
Emanuel Aldea
Gianni Franchi
BDL
UQCV
22
5
0
12 Oct 2023
Quantifying Uncertainty in Deep Learning Classification with Noise in
  Discrete Inputs for Risk-Based Decision Making
Quantifying Uncertainty in Deep Learning Classification with Noise in Discrete Inputs for Risk-Based Decision Making
Maryam Kheirandish
Shengfan Zhang
D. Catanzaro
V. Crudu
UQCV
19
0
0
09 Oct 2023
Adaptive Multi-head Contrastive Learning
Adaptive Multi-head Contrastive Learning
Lei Wang
Piotr Koniusz
Tom Gedeon
Liang Zheng
35
4
0
09 Oct 2023
A review of uncertainty quantification in medical image analysis:
  probabilistic and non-probabilistic methods
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
Ling Huang
S. Ruan
Yucheng Xing
Mengling Feng
41
20
0
09 Oct 2023
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian
  Inference
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
Marvin Schmitt
Desi R. Ivanova
Daniel Habermann
Baixu Chen
Jie Jiang
Stefan T. Radev
FedML
35
5
0
06 Oct 2023
Uncertainty quantification for deep learning-based schemes for solving
  high-dimensional backward stochastic differential equations
Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations
Lorenc Kapllani
Long Teng
Matthias Rottmann
19
1
0
05 Oct 2023
Unified Uncertainty Calibration
Unified Uncertainty Calibration
Kamalika Chaudhuri
David Lopez-Paz
24
0
0
02 Oct 2023
Skip-Plan: Procedure Planning in Instructional Videos via Condensed
  Action Space Learning
Skip-Plan: Procedure Planning in Instructional Videos via Condensed Action Space Learning
Zhiheng Li
Wenjia Geng
Muheng Li
Lei Chen
Yansong Tang
Jiwen Lu
Jie Zhou
22
9
0
01 Oct 2023
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