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Simple and Principled Uncertainty Estimation with Deterministic Deep
  Learning via Distance Awareness

Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

17 June 2020
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness"

50 / 296 papers shown
Title
Are vision language models robust to uncertain inputs?
Are vision language models robust to uncertain inputs?
Xi Wang
Eric Nalisnick
AAML
VLM
1
0
0
17 May 2025
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know
Shireen Kudukkil Manchingal
Fabio Cuzzolin
56
0
0
08 May 2025
Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models
Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models
Aishwarya Venkataramanan
P. Bodesheim
Joachim Denzler
BDL
VLM
64
0
0
08 May 2025
ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding
ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding
Santosh Rajagopalan
Jonathan Vronsky
Songbai Yan
S. Alireza Golestaneh
Shubhra Chandra
Min Zhou
66
0
0
26 Apr 2025
Geometry-aware Active Learning of Spatiotemporal Dynamic Systems
Geometry-aware Active Learning of Spatiotemporal Dynamic Systems
Xizhuo
Zhang
AI4CE
29
0
0
26 Apr 2025
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
Haoyang Luo
Linwei Tao
Minjing Dong
Chang Xu
25
0
0
18 Apr 2025
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
Kumar Manas
Christian Schlauch
Adrian Paschke
Christian Wirth
Nadja Klein
40
0
0
17 Apr 2025
Prior2Former -- Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation
Prior2Former -- Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation
Sebastian Schmidt
Julius Körner
Dominik Fuchsgruber
Stefano Gasperini
F. Tombari
Stephan Günnemann
26
0
0
07 Apr 2025
Outlook Towards Deployable Continual Learning for Particle Accelerators
Outlook Towards Deployable Continual Learning for Particle Accelerators
Kishansingh Rajput
Sen Lin
Auralee Edelen
Willem Blokland
Malachi Schram
31
0
0
04 Apr 2025
Offline Model-Based Optimization: Comprehensive Review
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim
Jiayao Gu
Ye Yuan
Taeyoung Yun
Ziqiang Liu
Yoshua Bengio
Can Chen
OffRL
67
2
0
21 Mar 2025
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
Severin Heidrich
Till Beemelmanns
Alexey Nekrasov
Bastian Leibe
Lutz Eckstein
55
0
0
13 Mar 2025
LiDAR-enhanced 3D Gaussian Splatting Mapping
Jian Shen
Huai Yu
Ji Wu
Wen Yang
Gui-Song Xia
3DGS
52
0
0
07 Mar 2025
Revisiting Kernel Attention with Correlated Gaussian Process Representation
Revisiting Kernel Attention with Correlated Gaussian Process Representation
Long Minh Bui
Tho Tran Huu
Duy-Tung Dinh
T. Nguyen
Trong Nghia Hoang
52
2
0
27 Feb 2025
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
Tianyu Zhao
Mahmoud Srewa
Salma Elmalaki
95
1
0
25 Feb 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective
Learning Hyperparameters via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
65
0
0
03 Feb 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang
Keivan K1 Shariatmadar
Shireen Kudukkil Manchingal
Fabio Cuzzolin
David Moens
Hans Hallez
UQCV
BDL
92
12
0
28 Jan 2025
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Yibin Wang
Haizhou Shi
Ligong Han
Dimitris N. Metaxas
Hao Wang
BDL
UQLM
116
6
0
28 Jan 2025
On the challenges of detecting MCI using EEG in the wild
On the challenges of detecting MCI using EEG in the wild
Aayush Mishra
David Joffe
Sankara Surendra Telidevara
David S Oakley
Anqi Liu
46
0
0
15 Jan 2025
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation
S. Landgraf
Rongjun Qin
Markus Ulrich
UQCV
75
0
0
14 Jan 2025
Multi-layer Radial Basis Function Networks for Out-of-distribution Detection
Multi-layer Radial Basis Function Networks for Out-of-distribution Detection
Amol Khanna
Chenyi Ling
Derek Everett
Edward Raff
Nathan Inkawhich
OODD
33
0
0
05 Jan 2025
Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images
Xiaoge Zhang
Tao Wang
Chao Yan
Fedaa Najdawi
Kai Zhou
Yuan Ma
Yiu-ming Cheung
Bradley Malin
MedIm
42
0
0
03 Jan 2025
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
M. Valiuddin
R. V. Sloun
C.G.A. Viviers
Peter H. N. de With
Fons van der Sommen
UQCV
91
1
0
25 Nov 2024
Data-Driven Gradient Optimization for Field Emission Management in a
  Superconducting Radio-Frequency Linac
Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac
Steven Goldenberg
Kawser Ahammed
A. Carpenter
Jiang Li
Riad Suleiman
C. Tennant
AI4CE
25
0
0
11 Nov 2024
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy
  Minimization of CKA
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA
David Smerkous
Qinxun Bai
Fuxin Li
BDL
31
0
0
31 Oct 2024
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Arthur Pignet
Chiara Regniez
John Klein
72
1
0
30 Oct 2024
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice
Hsiu-Yuan Huang
Yutong Yang
Zhaoxi Zhang
Sanwoo Lee
Yunfang Wu
41
9
0
20 Oct 2024
Normalizing self-supervised learning for provably reliable Change Point
  Detection
Normalizing self-supervised learning for provably reliable Change Point Detection
Alexandra Bazarova
Evgenia Romanenkova
Alexey Zaytsev
26
1
0
17 Oct 2024
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Johan Hatleskog
Kostas Alexis
3DPC
47
0
0
14 Oct 2024
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene
  Semantic Segmentation
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation
Hanieh Shojaei
Qianqian Zou
Max Mehltretter
UQCV
23
0
0
11 Oct 2024
Conjugated Semantic Pool Improves OOD Detection with Pre-trained
  Vision-Language Models
Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models
Mengyuan Chen
Junyu Gao
Changsheng Xu
VLM
OODD
30
0
0
11 Oct 2024
Understanding Human Activity with Uncertainty Measure for Novelty in
  Graph Convolutional Networks
Understanding Human Activity with Uncertainty Measure for Novelty in Graph Convolutional Networks
Hao Xing
Darius Burschka
31
1
0
10 Oct 2024
Unpacking Failure Modes of Generative Policies: Runtime Monitoring of
  Consistency and Progress
Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress
Christopher Agia
Rohan Sinha
Jingyun Yang
Zi-ang Cao
Rika Antonova
Marco Pavone
Jeannette Bohg
31
7
0
06 Oct 2024
Distribution Guided Active Feature Acquisition
Distribution Guided Active Feature Acquisition
Yang Li
Junier Oliva
29
0
0
04 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty
  Quantification in Deep Learning
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
Nils Lehmann
Jakob Gawlikowski
Adam J. Stewart
Vytautas Jancauskas
Stefan Depeweg
Eric T. Nalisnick
N. Gottschling
42
0
0
04 Oct 2024
Revisiting Essential and Nonessential Settings of Evidential Deep
  Learning
Revisiting Essential and Nonessential Settings of Evidential Deep Learning
Mengyuan Chen
Junyu Gao
Changsheng Xu
EDL
54
1
0
01 Oct 2024
End-to-End Conformal Calibration for Optimization Under Uncertainty
End-to-End Conformal Calibration for Optimization Under Uncertainty
Christopher Yeh
Nicolas H. Christianson
Alan Wu
Adam Wierman
Yisong Yue
28
3
0
30 Sep 2024
MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation
MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation
Taha Koleilat
Hojat Asgariandehkordi
H. Rivaz
Yiming Xiao
MedIm
VLM
46
6
0
28 Sep 2024
SSE: Multimodal Semantic Data Selection and Enrichment for
  Industrial-scale Data Assimilation
SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation
Maying Shen
Nadine Chang
Sifei Liu
Jose M. Alvarez
36
0
0
20 Sep 2024
Uncertainty Estimation by Density Aware Evidential Deep Learning
Uncertainty Estimation by Density Aware Evidential Deep Learning
Taeseong Yoon
Heeyoung Kim
EDL
UQCV
39
1
0
13 Sep 2024
A Comprehensive Survey on Evidential Deep Learning and Its Applications
A Comprehensive Survey on Evidential Deep Learning and Its Applications
Junyu Gao
Mengyuan Chen
Liangyu Xiang
Changsheng Xu
EDL
BDL
UQCV
44
5
0
07 Sep 2024
Adapting Vision-Language Models to Open Classes via Test-Time Prompt
  Tuning
Adapting Vision-Language Models to Open Classes via Test-Time Prompt Tuning
Zhengqing Gao
Xiang Ao
Xu-Yao Zhang
Cheng-Lin Liu
VLM
VPVLM
39
0
0
29 Aug 2024
Gaussian Mixture based Evidential Learning for Stereo Matching
Gaussian Mixture based Evidential Learning for Stereo Matching
Weide Liu
Xingxing Wang
Lu Wang
Jun Cheng
Fayao Liu
Xulei Yang
26
0
0
05 Aug 2024
Know Your Limits: A Survey of Abstention in Large Language Models
Know Your Limits: A Survey of Abstention in Large Language Models
Bingbing Wen
Jihan Yao
Shangbin Feng
Chenjun Xu
Yulia Tsvetkov
Bill Howe
Lucy Lu Wang
59
5
0
25 Jul 2024
Probabilistic Parameter Estimators and Calibration Metrics for Pose
  Estimation from Image Features
Probabilistic Parameter Estimators and Calibration Metrics for Pose Estimation from Image Features
Romeo Valentin
Sydney M. Katz
Joonghyun Lee
Don Walker
Matthew Sorgenfrei
Mykel J. Kochenderfer
36
0
0
23 Jul 2024
Understanding the Dependence of Perception Model Competency on Regions
  in an Image
Understanding the Dependence of Perception Model Competency on Regions in an Image
Sara Pohland
Claire Tomlin
19
1
0
15 Jul 2024
Improving Explainability of Softmax Classifiers Using a Prototype-Based
  Joint Embedding Method
Improving Explainability of Softmax Classifiers Using a Prototype-Based Joint Embedding Method
Hilarie Sit
Brendan Keith
Karianne Bergen
32
0
0
02 Jul 2024
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Wataru Hashimoto
Hidetaka Kamigaito
Taro Watanabe
60
0
0
02 Jul 2024
Are you sure? Analysing Uncertainty Quantification Approaches for
  Real-world Speech Emotion Recognition
Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion Recognition
Oliver Schrufer
M. Milling
Felix Burkhardt
F. Eyben
Björn Schuller
29
3
0
01 Jul 2024
A Rate-Distortion View of Uncertainty Quantification
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou
Benjamin Eysenbach
Frank Nielsen
Artur Dubrawski
UQCV
46
2
0
16 Jun 2024
Beyond the Norms: Detecting Prediction Errors in Regression Models
Beyond the Norms: Detecting Prediction Errors in Regression Models
A. Altieri
Marco Romanelli
Georg Pichler
F. Alberge
Pablo Piantanida
49
0
0
11 Jun 2024
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