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Deep Evidential Regression
v1v2 (latest)

Deep Evidential Regression

7 October 2019
Alexander Amini
Wilko Schwarting
A. Soleimany
Daniela Rus
    EDLPERBDLUDUQCV
ArXiv (abs)PDFHTML

Papers citing "Deep Evidential Regression"

50 / 205 papers shown
Title
A System-Level View on Out-of-Distribution Data in Robotics
A System-Level View on Out-of-Distribution Data in Robotics
Rohan Sinha
Apoorva Sharma
Somrita Banerjee
T. Lew
Rachel Luo
Spencer M. Richards
Yixiao Sun
Edward Schmerling
Marco Pavone
UQCV
102
26
0
28 Dec 2022
Improving Uncertainty Quantification of Variance Networks by
  Tree-Structured Learning
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning
Wenxuan Ma
Xing Yan
Kun Zhang
UQCV
66
0
0
24 Dec 2022
Calibration and generalizability of probabilistic models on low-data
  chemical datasets with DIONYSUS
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
Gary Tom
Riley J. Hickman
Aniket N. Zinzuwadia
A. Mohajeri
Benjamín Sánchez-Lengeling
A. Aspuru‐Guzik
84
17
0
03 Dec 2022
Investigating Deep Learning Model Calibration for Classification
  Problems in Mechanics
Investigating Deep Learning Model Calibration for Classification Problems in Mechanics
S. Mohammadzadeh
Peerasait Prachaseree
Emma Lejeune
AI4CE
71
3
0
01 Dec 2022
Evidential Conditional Neural Processes
Evidential Conditional Neural Processes
Deepshikha Pandey
Qi Yu
BDLEDLUQCV
68
15
0
30 Nov 2022
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step
  Inference
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference
Nikita Durasov
Nik Dorndorf
Hieu M. Le
Pascal Fua
UQCV
97
10
0
21 Nov 2022
Interpretable Self-Aware Neural Networks for Robust Trajectory
  Prediction
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction
Masha Itkina
Mykel J. Kochenderfer
EDLUQCV
109
26
0
16 Nov 2022
Leveraging Heteroscedastic Uncertainty in Learning Complex Spectral
  Mapping for Single-channel Speech Enhancement
Leveraging Heteroscedastic Uncertainty in Learning Complex Spectral Mapping for Single-channel Speech Enhancement
Kuan-Lin Chen
Daniel D. E. Wong
Ke Tan
Buye Xu
Anurag Kumar
V. Ithapu
97
2
0
16 Nov 2022
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for
  Autonomous Driving
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving
Liang Peng
Boqi Li
Wen-Hui Yu
Kailiang Yang
Wenbo Shao
Hong Wang
AAML
67
26
0
08 Nov 2022
PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in
  Long-tail Traffic Scenarios
PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios
Liangzu Peng
Jun Li
Wenbo Shao
Hong Wang
83
9
0
07 Nov 2022
Materials Property Prediction with Uncertainty Quantification: A
  Benchmark Study
Materials Property Prediction with Uncertainty Quantification: A Benchmark Study
Daniel Varivoda
Rongzhi Dong
Sadman Sadeed Omee
Jianjun Hu
AI4CE
90
23
0
04 Nov 2022
Uncertainty-Aware DNN for Multi-Modal Camera Localization
Uncertainty-Aware DNN for Multi-Modal Camera Localization
Matteo Vaghi
Augusto Luis Ballardini
S. Fontana
D. Sorrenti
UQCVEDL
81
1
0
02 Nov 2022
Measuring the Confidence of Traffic Forecasting Models: Techniques,
  Experimental Comparison and Guidelines towards Their Actionability
Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability
I. Laña
Ignacio
I. Olabarrieta
Javier Del Ser
64
1
0
28 Oct 2022
Probabilistic Traversability Model for Risk-Aware Motion Planning in
  Off-Road Environments
Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments
Xiaoyi Cai
Michael Everett
Lakshay Sharma
Philip R. Osteen
Jonathan P. How
101
40
0
01 Oct 2022
Out-of-Distribution Detection with Hilbert-Schmidt Independence
  Optimization
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Jingyang Lin
Yu Wang
Qi Cai
Yingwei Pan
Ting Yao
Hongyang Chao
Tao Mei
OODD
64
3
0
26 Sep 2022
Some Supervision Required: Incorporating Oracle Policies in
  Reinforcement Learning via Epistemic Uncertainty Metrics
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics
Jun Jet Tai
Jordan Terry
M. Innocente
J. Brusey
N. Horri
80
2
0
22 Aug 2022
Incorporating functional summary information in Bayesian neural networks
  using a Dirichlet process likelihood approach
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach
Vishnu Raj
Tianyu Cui
Markus Heinonen
Pekka Marttinen
UQCVBDL
42
1
0
04 Jul 2022
Uncertainty-aware Panoptic Segmentation
Uncertainty-aware Panoptic Segmentation
Kshitij Sirohi
Sajad Marvi
Daniel Buscher
Wolfram Burgard
EDLUQCV
80
26
0
29 Jun 2022
Distributional Gaussian Processes Layers for Out-of-Distribution
  Detection
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
102
0
0
27 Jun 2022
A Survey on Uncertainty Reasoning and Quantification for Decision
  Making: Belief Theory Meets Deep Learning
A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning
Zhen Guo
Zelin Wan
Qisheng Zhang
Xujiang Zhao
F. Chen
Jin-Hee Cho
Qi Zhang
Lance M. Kaplan
Dong-Ho Jeong
A. Jøsang
UQCVEDL
75
10
0
12 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement
  Learning
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning
Bertrand Charpentier
Ransalu Senanayake
Mykel Kochenderfer
Stephan Günnemann
PERUD
85
26
0
03 Jun 2022
Excess risk analysis for epistemic uncertainty with application to
  variational inference
Excess risk analysis for epistemic uncertainty with application to variational inference
Futoshi Futami
Tomoharu Iwata
N. Ueda
Issei Sato
Masashi Sugiyama
UQCV
117
1
0
02 Jun 2022
The Unreasonable Effectiveness of Deep Evidential Regression
The Unreasonable Effectiveness of Deep Evidential Regression
N. Meinert
J. Gawlikowski
Alexander Lavin
UQCVEDL
288
37
0
20 May 2022
A Survey on Uncertainty Toolkits for Deep Learning
A Survey on Uncertainty Toolkits for Deep Learning
Maximilian Pintz
Joachim Sicking
Maximilian Poretschkin
Maram Akila
ELM
78
6
0
02 May 2022
Tailored Uncertainty Estimation for Deep Learning Systems
Tailored Uncertainty Estimation for Deep Learning Systems
Joachim Sicking
Maram Akila
Jan David Schneider
Fabian Hüger
Peter Schlicht
Tim Wirtz
Stefan Wrobel
UQCV
79
2
0
29 Apr 2022
Autoencoder Attractors for Uncertainty Estimation
Autoencoder Attractors for Uncertainty Estimation
S. Cruz
B. Taetz
Thomas Stifter
D. Stricker
UQCV
86
9
0
01 Apr 2022
Multidimensional Belief Quantification for Label-Efficient Meta-Learning
Multidimensional Belief Quantification for Label-Efficient Meta-Learning
Deepshikha Pandey
Qi Yu
UQCV
50
11
0
23 Mar 2022
OpenTAL: Towards Open Set Temporal Action Localization
OpenTAL: Towards Open Set Temporal Action Localization
Wentao Bao
Qi Yu
Yu Kong
EDL
74
29
0
10 Mar 2022
Augmenting Neural Networks with Priors on Function Values
Augmenting Neural Networks with Priors on Function Values
Hunter Nisonoff
Yixin Wang
Jennifer Listgarten
74
3
0
10 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Deebul Nair
Nico Hochgeschwender
Miguel A. Olivares-Mendez
OOD
81
7
0
03 Feb 2022
Deep Learning meets Liveness Detection: Recent Advancements and
  Challenges
Deep Learning meets Liveness Detection: Recent Advancements and Challenges
Arian Sabaghi
Marzieh Oghbaie
Kooshan Hashemifard
Mohammad Akbari
AAML
75
7
0
29 Dec 2021
Improving evidential deep learning via multi-task learning
Improving evidential deep learning via multi-task learning
Dongpin Oh
Bonggun Shin
EDLUQCV
102
24
0
17 Dec 2021
Semi-supervised Impedance Inversion by Bayesian Neural Network Based on
  2-d CNN Pre-training
Semi-supervised Impedance Inversion by Bayesian Neural Network Based on 2-d CNN Pre-training
Muyang Ge
Wenlong Wang
Wangxiangming Zheng
SSL
41
9
0
20 Nov 2021
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma
  Distributions
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma
Zongbo Han
Changqing Zhang
Huazhu Fu
Qiufeng Wang
Q. Hu
EDLUQCV
140
44
0
11 Nov 2021
Uncertainty Quantification in Neural Differential Equations
Uncertainty Quantification in Neural Differential Equations
Olga Graf
P. Flores
P. Protopapas
K. Pichara
UQCVAI4CE
64
7
0
08 Nov 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node
  Classification
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCVBDL
125
89
0
26 Oct 2021
Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task
  Uncertainty Estimation
Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation
Kürsat Petek
Kshitij Sirohi
Daniel Buscher
Wolfram Burgard
UQCV
117
25
0
20 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning
  Methods For Uncertainty Estimation
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation
Dennis Ulmer
Christian Hardmeier
J. Frellsen
BDLUQCVUDEDLPER
152
55
0
06 Oct 2021
Reliable Neural Networks for Regression Uncertainty Estimation
Reliable Neural Networks for Regression Uncertainty Estimation
Tony Tohme
Kevin Vanslette
K. Youcef-Toumi
UQCVBDL
85
15
0
16 Sep 2021
PI3NN: Out-of-distribution-aware prediction intervals from three neural
  networks
PI3NN: Out-of-distribution-aware prediction intervals from three neural networks
Si-Yuan Liu
Pei Zhang
Dan Lu
Guannan Zhang
OODD
65
10
0
05 Aug 2021
Evidential Deep Learning for Open Set Action Recognition
Evidential Deep Learning for Open Set Action Recognition
Wentao Bao
Qi Yu
Yu Kong
CMLEDL
116
141
0
21 Jul 2021
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement
  Learning
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning
Peide Cai
Hengli Wang
Huaiyang Huang
Yuxuan Liu
Ming-Yuan Liu
53
66
0
18 Jul 2021
Calibrated Uncertainty for Molecular Property Prediction using Ensembles
  of Message Passing Neural Networks
Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks
Jonas Busk
Peter Bjørn Jørgensen
Arghya Bhowmik
Mikkel N. Schmidt
Ole Winther
Tejs Vegge
82
52
0
13 Jul 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
242
1,179
0
07 Jul 2021
Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous
  Trajectories
Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Trajectories
S. Singh
Jaya Shradha Fowdur
J. Gawlikowski
Daniel Medina
107
1
0
04 Jul 2021
Adaptive machine learning for protein engineering
Adaptive machine learning for protein engineering
B. Hie
Kevin Kaichuang Yang
92
81
0
10 Jun 2021
Evidential Turing Processes
Evidential Turing Processes
M. Kandemir
Abdullah Akgul
Manuel Haussmann
Gözde B. Ünal
EDLUQCVBDL
70
10
0
02 Jun 2021
Efficient and Robust LiDAR-Based End-to-End Navigation
Efficient and Robust LiDAR-Based End-to-End Navigation
Zhijian Liu
Alexander Amini
Sibo Zhu
S. Karaman
Song Han
Daniela Rus
253
48
0
20 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential
  Family Distributions
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
Bertrand Charpentier
Oliver Borchert
Daniel Zügner
Simon Geisler
Stephan Günnemann
UQCVBDL
72
17
0
10 May 2021
Multivariate Deep Evidential Regression
Multivariate Deep Evidential Regression
N. Meinert
Alexander Lavin
BDLPEREDLUQCV
90
21
0
13 Apr 2021
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