Evidential Deep Learning

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3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation
Oct 7, 2026Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg +1Segmentation Uncertainty Estimation Evidential Deep Learning
Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany · Hamad Bin Khalifa University (HBKU), Education City, Gate 8, P.O. Box 5825, Doha, Qatar · Linköping University, SE-581 83, Linköping, Sweden
Localisation-Aware Uncertainty for Pretrained Object Detection
Oct 1, 2026Charmaine Barker, Daniel Bethell, Simos GerasimouEvidential Deep Learning Uncertainty Quantification
Department of Computer Science, University of York, UK · Department of Elect. Eng., and Computer Science and Eng., Cyprus University of Technology, Cyprus
Robust Evidential Learning Through Latent Consistency
Oct 1, 2026Charmaine Barker, Daniel Bethell, Simos GerasimouEvidential Deep Learning Adversarial Robustness
Department of Computer Science, University of York, UK · Department of Elect. Eng., and Computer Science and Eng., Cyprus University of Technology, Cyprus
Ev-YOLO: Uncertainty-Aware Object Detection via a Unified Evidential Formulation
Sep 21, 2026Simon Barbarit-Gaboriau, Hind Laghmara, Rémi Boutteau +1Evidential Deep Learning Object Detection
LITIS - STI, INSA Rouen Normandie · INSA Rouen Normandie, Univ Rouen Normandie, Univ Le Havre Normandie, Normandie Univ, LITIS UR 4108, F-76000 Rouen, France. · LITIS - STI +1
Evidential Deep Learning for Multi-Modal Anti-UAV Detection
Sep 1, 2026Dmitry Golovchits, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor AlsahagEvidential Deep Learning Dempster-Shafer Theory
University of Amsterdam Amsterdam, The Netherlands
ELVAE: Evidential Learning-Based Variational Autoencoder for Uncertainty-Aware Generation
Aug 11, 2026Ge WangVariational Autoencoders Evidential Deep Learning
Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, New York, USA
Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery
Aug 3, 2026Laura Bader, Muhammad Ammar Ahmed, Xiao Xiang Zhu +1Remote Sensing Image Understanding Evidential Deep Learning
LMU Munich, 80539 Munich, Germany · Munich Center for Machine Learning (MCML) · TU Munich, 80333 Munich
ELECTRIC: Evidential Learning-Enhanced CT Reconstruction via Iterative Correction
Jul 27, 2026Ge WangEvidential Deep Learning Bayesian Inverse Problems
Department of Biomedical Engineering Department of Electrical, Computer and Systems Engineering Department of Computer Science Rensselaer Polytechnic Institute, Troy, New York, USA
Trustworthy Protein-Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion
Jul 20, 2026Yongchan Hong, Defu Cao, Wenjin Liu +6Protein-Ligand Binding Affinity Prediction Evidential Deep Learning
Department of Quantitative & Computational Biology University of Southern California Los Angeles, California, USA · Department of Computer Science University of Southern California Los Angeles, California, USA · Department of Chemistry University of California, Berkeley Berkeley, California, USA
Adapting Evidential Neural Networks to Test-Time Neighbor Fusion Improves Molecular Property Prediction
Jul 13, 2026Cameron Gruich, Weichi Yao, Yixin Wang +1Evidential Deep Learning Bayesian Inference
Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2136, USA · Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109-1107 USA
EvidentialRAG: Quantifying and Mitigating Information Conflict in Multi-Source Retrieval-Augmented Generation via Evidential Deep Learning
Jul 11, 2026S M Asif Hossain, Ruksat Khan Shayoni, M. F. MridhaRetrieval-Augmented Generation Evidential Deep Learning
aSchool of Computing, Wichita State University, Kansas, USA · bDepartment of Computer Science, American International University-Bangladesh, Dhaka, Bangladesh
Robustness Meets Uncertainty: Evidential Adversarial Training for Robust Selective Classification
Jul 3, 2026Nicolas Sournac, Ahmed Baha Ben Jmaa, Bertrand BraeckeveldtAdversarial Training Evidential Deep Learning
Multitel Research & Innovation Center, Artificial Intelligence Department, Belgium · TRAIL – Trusted AI Labs, Belgium
Von Mises Based Uncertainty Quantification for Closely Spaced Automotive Radar Targets
Jun 30, 2026Vinay Kulkarni, V. V. ReddyEvidential Deep Learning Uncertainty Quantification
International Institute of Information Technology, Bengaluru, India
ProMUSE: Progressive Multi-modal Uncertainty-guided Staged Evidential Alzheimer Disease Classification
Jun 11, 2026Long Doan, Branden Chen, Ethan Litton +6Efficient Multimodal Inference Evidential Deep Learning
Department of Computer Science, Kennesaw State University · Department of Data Science and Analytics, Kennesaw State University · Department of Information Technology, Kennesaw State University +2
Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection
Jun 1, 2026Xiaolu Kang, Zhongyuan Wang, Jikang Cheng +5Evidential Deep Learning Multi-View Learning
School of Computer Science, Wuhan University, Wuhan, China · School of Integrated Circuits, Peking University, Beijing, China · School of Information, Huazhong Agricultural University, Wuhan, China +2
Variational Inference for Evidential Deep Learning
May 26, 2026Jiawei Tang, Xinyan Du, Hui Liu +2Evidential Deep Learning Uncertainty Quantification
School of Computer Science and Engineering Southeast University Nanjing 210096, China · School of Computing Information Sciences Saint Francis University2026 Hong Kong SAR, China · CityDepartmentUniversityof Computerof Hong KongScience Hong Kong SAR, China
Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning
May 25, 2026Taha Koleilat, Hassan Rivaz, Yiming XiaoEvidential Deep Learning VLM Adaptation
Concordia University, Montreal, Canada
Generalized Evidential Deep Learning: From a Bayesian Perspective
May 25, 2026Yuanye Liu, Yibo Gao, Yuanyang Chen +1Evidential Deep Learning Uncertainty Quantification
School of Data Science, Fudan University, Shanghai, China.
Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks
May 22, 2026Rouaa Hoblos, Noura Dridi, Noureddine Zerhouni +1Evidential Deep Learning Uncertainty Quantification
FEMTO-ST · Universit´e Marie et Louis Pasteur, SUPMICROTECH, CNRS, Institut FEMTO-ST, F-25000 Besan¸con, France
Plug-in Losses for Evidential Deep Learning: A Simplified Framework for Uncertainty Estimation that Includes the Softmax Classifier
May 21, 2026Berk Hayta, Hannah Laus, Simon Mittermaier +1Evidential Deep Learning
TU Munich · TU Munich & MCML · Infineon Technologies +1
Invascal: Inverse-Vacuity Self-Calibration for Uncertainty-Aware LiDAR Range-View Semantic Segmentation
May 20, 2026Kerim Turacan, Hannes Reichert, Andrei Bolandut +1Evidential Deep Learning 3D Semantic Segmentation
Faculty of Engineering and Computer Science, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany
Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R
May 19, 2026Zihao Zhu, Wenyuan Zhao, Nuo Chen +2Evidential Deep Learning 3D Reconstruction
Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
May 16, 2026Yunzhi Tian, Dekui Wang, Qirong Bu +3Sleep Stage Classification Evidential Deep Learning
College of Computer Science, Northwest University, Xi’an, China.
Uncertainty-Aware Wildfire Smoke Density Classification from Satellite Imagery via CBAM-Augmented EfficientNet with Evidential Deep Learning
May 15, 2026Ranjith ChodavarapuRemote Sensing Image Understanding Evidential Deep Learning
Kent State University
A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classification
May 11, 2026Ezel Kilicdere, Shireen Kudukkil Manchingal, Fabio CuzzolinHierarchical Classification Evidential Deep Learning
Datasand IT and Consultancy Ltd. · Institute for AI, Data Analysis and Systems (AIDAS) School of Engineering, Computing and Mathematics, Oxford Brookes University, UK
Probabilistic Dating of Historical Manuscripts via Evidential Deep Regression on Visual Script Features
May 7, 2026Ranjith ChodavarapuHistorical Document Analysis Evidential Deep Learning
Kent State University
Rethinking Vacuity for OOD Detection in Evidential Deep Learning
May 7, 2026Claire McNamaraLLM Evaluation Evidential Deep Learning
∗Accenture Labs · †Trinity College Dublin.
Revisiting Uncertainty: On Evidential Learning for Partially Relevant Video Retrieval
May 7, 2026Jun Li, Peifeng Lai, Xuhang Lou +5Cross-Modal Learning Evidential Deep Learning
Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · Peng Cheng Laboratory, Shenzhen, China · Harbin Institute of Technology, Shenzhen, China
Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
May 6, 2026Yucheng Ruan, Ling Huang, Qika Lin +2Evidential Deep Learning Uncertainty Quantification
Saw Swee Hock School of Public Health, National University of Singapore, Singapore
GEM-FI: Gated Evidential Mixtures with Fisher Modulation
May 5, 2026Marco Mustafa Mohammed, Fatemeh Daneshfar, Pietro LiòEvidential Deep Learning OOD Detection
Department of Computer Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

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A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation

Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg, Kira Maag

Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany · Hamad Bin Khalifa University (HBKU), Education City, Gate 8, P.O. Box 5825, Doha, Qatar · Linköping University, SE-581 83, Linköping, Sweden

Segmentation Uncertainty Estimation Evidential Deep Learning Semantic Segmentation

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Semantic segmentation networks operate on a fixed set of classes and therefore fail when out-of-distribution (OOD) objects appear during deployment, a critical limitation for safety-critical applications such as autonomous driving. Reliably identifying OOD objects requires well-calibrated epistemic uncertainty, yet common softmax-based confidence scores remain overconfident, while Bayesian alternatives such as Monte Carlo dropout or deep ensembles require costly repeated forward passes. Evidential Deep Learning (EDL) offers an efficient alternative by modeling class probabilities as a Dirichlet distribution learned from a single deterministic forward pass. Existing EDL formulations rely on Euclidean objectives that push predictions towards the simplex vertices, encouraging overconfidence rather than preserving uncertainty for unfamiliar inputs. We instead employ Wasserstein-based objectives, which respect the geometry of the probability simplex, and study the influence of the Wasserstein order on segmentation accuracy and OOD detection within a unified evidential framework. We evaluate this framework on a convolutional (DeepLabV3+) and a transformer-based (SegFormer) architecture on the SegmentMeIfYouCan benchmark, including LostAndFound, RoadObstacle21, RoadAnomaly21, and Fishyscapes. Our results show the optimal Wasserstein order is architecture-dependent: second-order objectives dominate on the convolutional backbone, third-order objectives on the transformer backbone, and our framework surpasses comparable baselines on most metrics, with a single deterministic forward pass.

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