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What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
v1v2 (latest)

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

15 March 2017
Alex Kendall
Y. Gal
    BDLOODUDUQCVPER
ArXiv (abs)PDFHTML

Papers citing "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"

50 / 2,439 papers shown
Domain Adaptation of Echocardiography Segmentation Via Reinforcement
  Learning
Domain Adaptation of Echocardiography Segmentation Via Reinforcement Learning
Arnaud Judge
Thierry Judge
Nicolas Duchateau
Roman A. Sandler
Joseph Z. Sokol
Olivier Bernard
Pierre-Marc Jodoin
OOD
196
4
0
25 Jun 2024
Conditional Bayesian Quadrature
Conditional Bayesian Quadrature
Zonghao Chen
Masha Naslidnyk
Arthur Gretton
F. Briol
TPM
327
6
0
24 Jun 2024
Uncertainty-Aware Reward-Free Exploration with General Function
  Approximation
Uncertainty-Aware Reward-Free Exploration with General Function Approximation
Junkai Zhang
Weitong Zhang
Dongruo Zhou
Q. Gu
403
6
0
24 Jun 2024
Bayesian neural networks for predicting uncertainty in full-field
  material response
Bayesian neural networks for predicting uncertainty in full-field material response
G. Pasparakis
Lori Graham-Brady
Michael D. Shields
AI4CE
263
18
0
21 Jun 2024
VeriFlow: Modeling Distributions for Neural Network Verification
VeriFlow: Modeling Distributions for Neural Network Verification
Faried Abu Zaid
Daniel Neider
Mustafa Yalçıner
526
1
0
20 Jun 2024
Unleashing the Potential of Open-set Noisy Samples Against Label Noise
  for Medical Image Classification
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification
Zehui Liao
Shishuai Hu
Yong-quan Xia
275
0
0
18 Jun 2024
CUQDS: Conformal Uncertainty Quantification under Distribution Shift for Trajectory Prediction
CUQDS: Conformal Uncertainty Quantification under Distribution Shift for Trajectory Prediction
Huiqun Huang
Sihong He
Fei Miao
631
0
0
17 Jun 2024
Uncertainty modeling for fine-tuned implicit functions
Uncertainty modeling for fine-tuned implicit functions
A. Susmelj
Mael Macuglia
Nataša Tagasovska
Reto Sutter
Sebastiano Caprara
Jean-Philippe Thiran
E. Konukoglu
376
2
0
17 Jun 2024
Understanding active learning of molecular docking and its applications
Understanding active learning of molecular docking and its applications
Jeonghyeon Kim
Juno Nam
Seongok Ryu
186
0
0
14 Jun 2024
Self-Knowledge Distillation for Learning Ambiguity
Self-Knowledge Distillation for Learning Ambiguity
Hancheol Park
Soyeong Jeong
Sukmin Cho
Jong C. Park
201
2
0
14 Jun 2024
Generative vs. Discriminative modeling under the lens of uncertainty
  quantification
Generative vs. Discriminative modeling under the lens of uncertainty quantification
Elouan Argouarc'h
François Desbouvries
Eric Barat
Eiji Kawasaki
UQCV
224
1
0
13 Jun 2024
Teaching with Uncertainty: Unleashing the Potential of Knowledge
  Distillation in Object Detection
Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection
Junfei Yi
Jianxu Mao
Tengfei Liu
Mingjie Li
Hanyu Gu
Hui Zhang
Xiaojun Chang
Yaonan Wang
293
5
0
11 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
366
1
0
11 Jun 2024
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving
Daniel Bogdoll
Noël Ollick
Tim Joseph
J. Marius Zöllner
350
3
0
10 Jun 2024
Domain Agnostic Conditional Invariant Predictions for Domain
  Generalization
Domain Agnostic Conditional Invariant Predictions for Domain Generalization
Zongbin Wang
Bin Pan
Zhenwei Shi
OOD
225
0
0
09 Jun 2024
On Subjective Uncertainty Quantification and Calibration in Natural
  Language Generation
On Subjective Uncertainty Quantification and Calibration in Natural Language GenerationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Ziyu Wang
Chris Holmes
UQLM
479
11
0
07 Jun 2024
Concept Drift Detection using Ensemble of Integrally Private Models
Concept Drift Detection using Ensemble of Integrally Private Models
Ayush K. Varshney
V. Torra
193
5
0
07 Jun 2024
Linear Opinion Pooling for Uncertainty Quantification on Graphs
Linear Opinion Pooling for Uncertainty Quantification on Graphs
C. Damke
Eyke Hüllermeier
377
2
0
06 Jun 2024
Shedding Light on Large Generative Networks: Estimating Epistemic
  Uncertainty in Diffusion Models
Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models
Lucas Berry
Axel Brando
David Meger
354
17
0
05 Jun 2024
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of
  LLMs
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs
Shuang Ao
Stefan Rueger
Advaith Siddharthan
271
4
0
05 Jun 2024
Learning Solutions of Stochastic Optimization Problems with Bayesian
  Neural Networks
Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks
Alan A. Lahoud
Erik Schaffernicht
J. A. Stork
UQCV
208
1
0
05 Jun 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
T. Pouplin
Alan Jeffares
Nabeel Seedat
Mihaela van der Schaar
874
7
0
05 Jun 2024
Improved context-sensitive transformer model for inland vessel
  trajectory prediction
Improved context-sensitive transformer model for inland vessel trajectory prediction
Kathrin Donandt
Karim Böttger
Dirk Söffker
175
4
0
04 Jun 2024
Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and
  Posterior Value Optimisation in Finite-State MDPs
Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs
Filippo Valdettaro
A. Aldo Faisal
OffRL
170
0
0
04 Jun 2024
Label-wise Aleatoric and Epistemic Uncertainty Quantification
Label-wise Aleatoric and Epistemic Uncertainty Quantification
Yusuf Sale
Paul Hofman
Timo Löhr
Lisa Wimmer
Thomas Nagler
Eyke Hüllermeier
PERUDUQCV
342
18
0
04 Jun 2024
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with
  Temporal Imputation
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation
Mohamed Ragab
Peiliang Gong
Emadeldeen Eldele
Wenyu Zhang
Ruibing Jin
Chuan-Sheng Foo
Daoqiang Zhang
Xiaoli Li
Zhenghua Chen
TTAAI4TS
414
4
0
04 Jun 2024
Diffusion Boosted Trees
Diffusion Boosted Trees
Xizewen Han
Mingyuan Zhou
AI4CE
405
0
0
03 Jun 2024
VOICE: Variance of Induced Contrastive Explanations to quantify
  Uncertainty in Neural Network Interpretability
VOICE: Variance of Induced Contrastive Explanations to quantify Uncertainty in Neural Network Interpretability
Mohit Prabhushankar
Ghassan AlRegib
FAttUQCV
203
3
0
01 Jun 2024
Memory-guided Network with Uncertainty-based Feature Augmentation for
  Few-shot Semantic Segmentation
Memory-guided Network with Uncertainty-based Feature Augmentation for Few-shot Semantic Segmentation
Xinyue Chen
Miaojing Shi
342
0
0
01 Jun 2024
A Structured Review of Literature on Uncertainty in Machine Learning &
  Deep Learning
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning
Fahimeh Fakour
Ali Mosleh
Ramin Ramezani
UQCVUDPER
447
14
0
01 Jun 2024
Scalable Bayesian Learning with posteriors
Scalable Bayesian Learning with posteriors
Samuel Duffield
Kaelan Donatella
Johnathan Chiu
Phoebe Klett
Daniel Simpson
BDLUQCV
546
9
0
31 May 2024
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Aastha Acharya
Caleb Lee
Marissa DÁlonzo
Jared Shamwell
Nisar R. Ahmed
Rebecca L. Russell
BDL
286
2
0
30 May 2024
NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the
  Wild
NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild
Weining Ren
Zihan Zhu
Boyang Sun
Jiaqi Chen
Marc Pollefeys
Songyou Peng
434
71
0
29 May 2024
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal
  Prediction
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction
Jeffrey Wen
Rizwan Ahmad
Philip Schniter
381
5
0
28 May 2024
Confidence-aware multi-modality learning for eye disease screening
Confidence-aware multi-modality learning for eye disease screening
K. Zou
Tian Lin
Zongbo Han
Meng Wang
Xuedong Yuan
Haoyu Chen
Changqing Zhang
Xiaojing Shen
Huazhu Fu
189
15
0
28 May 2024
Enhancing Global Sensitivity and Uncertainty Quantification in Medical
  Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba
Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba
Jiahao Huang
Liutao Yang
Fanwen Wang
Yang Nan
Weiwen Wu
...
Kuangyu Shi
Angelica I. Aviles-Rivero
Carola-Bibiane Schönlieb
Daoqiang Zhang
Guang Yang
Mamba
293
0
0
27 May 2024
Probabilistic Contrastive Learning with Explicit Concentration on the
  Hypersphere
Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere
H. Li
Ouyang Cheng
Tamaz Amiranashvili
Matthew S. Rosen
Bjoern Menze
J. Iglesias
346
1
0
26 May 2024
Transitional Uncertainty with Layered Intermediate Predictions
Transitional Uncertainty with Layered Intermediate Predictions
Ryan Benkert
Mohit Prabhushankar
Ghassan AlRegib
341
3
0
25 May 2024
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
E. Nehme
Rotem Mulayoff
T. Michaeli
UQCV
297
4
0
24 May 2024
Similarity-Navigated Conformal Prediction for Graph Neural Networks
Similarity-Navigated Conformal Prediction for Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2024
Jianqing Song
Jianguo Huang
Wenyu Jiang
Baoming Zhang
Shuangjie Li
Chongjun Wang
410
8
0
23 May 2024
Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech
  Foundation Models
Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation ModelsNeural Information Processing Systems (NeurIPS), 2024
Yuchen Hu
Chen Chen
Chao-Han Huck Yang
Chengwei Qin
Pin-Yu Chen
Chng Eng Siong
Chao Zhang
VLM
203
8
0
23 May 2024
LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention Networks
LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention Networks
Michelle Halbheer
Dominik J. Mühlematter
Alexander Becker
Dominik Narnhofer
Helge Aasen
Konrad Schindler
Mehmet Özgür Türkoglu
UQCV
543
14
0
23 May 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Credal Wrapper of Model Averaging for Uncertainty Estimation in ClassificationInternational Conference on Learning Representations (ICLR), 2024
Kaizheng Wang
Fabio Cuzzolin
Keivan K1 Shariatmadar
David Moens
Hans Hallez
UQCVBDL
391
6
0
23 May 2024
LOGIN: A Large Language Model Consulted Graph Neural Network Training
  Framework
LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
Yiran Qiao
Xiang Ao
Yang Liu
Jiarong Xu
Xiaoqian Sun
Qing He
290
12
0
22 May 2024
Counterfactual Gradients-based Quantification of Prediction Trust in
  Neural Networks
Counterfactual Gradients-based Quantification of Prediction Trust in Neural Networks
Mohit Prabhushankar
Ghassan AlRegib
UQCV
269
0
0
22 May 2024
System Safety Monitoring of Learned Components Using Temporal Metric
  Forecasting
System Safety Monitoring of Learned Components Using Temporal Metric Forecasting
Sepehr Sharifi
Andrea Stocco
Lionel C. Briand
AI4TS
296
3
0
21 May 2024
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose
  Prediction from Freehand 2D Ultrasound Videos
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos
Jayroop Ramesh
Nicola K. Dinsdale
INTERGROWTH-21 Consortium
P. Yeung
Ana I. L. Namburete
MedIm
317
5
0
21 May 2024
EdgeLoc: A Communication-Adaptive Parallel System for Real-Time
  Localization in Infrastructure-Assisted Autonomous Driving
EdgeLoc: A Communication-Adaptive Parallel System for Real-Time Localization in Infrastructure-Assisted Autonomous Driving
Boyi Liu
Jingwen Tong
Yufan Zhuang
284
6
0
20 May 2024
Transfer Learning for CSI-based Positioning with Multi-environment
  Meta-learning
Transfer Learning for CSI-based Positioning with Multi-environment Meta-learning
Anastasios Foliadis
Mario H. Castaneda
R. Stirling-Gallacher
Reiner S. Thomä
106
6
0
20 May 2024
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning
Nisha Lakshmana Raichur
Lucas Heublein
Tobias Feigl
A. Rügamer
Christopher Mutschler
Felix Ott
CLLBDL
485
15
0
17 May 2024
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