Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Hüllermeier, Eyke, Waegeman, Willem·2021·Machine Learning

Cited by (1,004)

Items 401–500 of 1,004

  1. Uncertainty-Aware Deep Learning Classification of Adamantinomatous Craniopharyngioma from Preoperative MRI
    Eric W. Prince, Debashis Ghosh, Carsten Görg, Todd Cameron Hankinson · 2023 · Diagnostics
  2. Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data
    Firas Gerges, Michel C. Boufadel, Elie R. Bou-Zeid, Hani H. Nassif, Jason T. L. Wang · 2023 · Knowledge and Information Systems
  3. What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety-Critical Systems
    Saddek Bensalem, Chih‐Hong Cheng, Wei Huang, Xiaowei Huang, Changshun Wu, Xingyu Zhao · 2023 · Lecture notes in computer science
  4. Evaluation of Machine Learning Architectures on the Quantification Of Epistemic and Aleatoric Uncertainties In Complex Dynamical Systems
    Stephen Guth, Alireza Mojahed, Themistoklis P. Sapsis · 2023 · Computer Methods in Applied Mechanics and Engineering
  5. SPARK: A High-Efficiency Black-Box Domain Adaptation Framework for Source Privacy-Preserving Drowsiness Detection
    Liqiang Yuan, Ruilin Li, Jian Cui, Mohammed Yakoob Siyal · 2024 · IEEE Journal of Biomedical and Health Informatics
  6. Intelligent and robust control of space manipulator for sustainable removal of space debris
    Shabadini Sampath, Jinglang Feng · 2024 · Acta Astronautica
  7. The Role of Uncertainty Quantification for Trustworthy AI
    Jessica Deuschel, Andreas Foltyn, Karsten Roscher, Stephan Scheele · 2024 · Springer eBooks
  8. Mineral Reconnaissance Through Scientific Consensus: First National Prospectivity Maps for PGE–Ni–Cu–Cr and Witwatersrand-type Au Deposits in South Africa
    Glen T. Nwaila, Steven E. Zhang, Julie Ellen Bourdeau, Emmanuel John M. Carranza, Stephanie E. Scheiber-Enslin, Musa S.D. Manzi, Fenitra Andriampenomanana, Yousef Ghorbani · 2024 · Natural Resources Research
  9. Identifying Research Gaps Through Self-Driving Car Data Analysis
    Mary L. Cummings, Ben Bauchwitz · 2024 · IEEE Transactions on Intelligent Vehicles
  10. An uncertainty-aware deep learning framework-based robust design optimization of metamaterial units
    Zihan Wang, Anindya Bhaduri, Hongyi Xu, Liping Wang · 2025 · Structural and Multidisciplinary Optimization
  11. Ringdown mode amplitudes of precessing binary black holes
    Francesco Nobili, Swetha Bhagwat, Costantino Pacilio, Davide Gerosa · 2025 · Physical review. D/Physical review. D.
  12. Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT
    Aparna Elangovan, Yuan Li, Douglas E. V. Pires, Melissa J. Davis, Karin M. Verspoor · 2022 · BMC Bioinformatics
  13. Dimensional Affect Uncertainty Modelling for Apparent Personality Recognition
    Mani Kumar Tellamekala, Timo Giesbrecht, Michel Valstar · 2022 · IEEE Transactions on Affective Computing
  14. Bayesian Deep Learning for Hyperspectral Image Classification With Low Uncertainty
    Xin Sheng He, Yushi Chen, Lingbo Huang · 2023 · IEEE Transactions on Geoscience and Remote Sensing
  15. Fairness through Aleatoric Uncertainty
    Anique Tahir, Lu Cheng, Huan Liu · 2023 · ACM International Conference on Information and Knowledge Management (CIKM)
  16. Bridging the Gap Between Explainable AI and Uncertainty Quantification to Enhance Trustability
    Dominik Seuß · 2021 · arXiv (Cornell University)
  17. Uncertainty evaluation for machine learning
    A Thompson, K Jagan, A Sundar, Rahul Khatry, J Donlevy, Spencer A. Thomas, P Harris · 2022
  18. A Comprehensive Survey on the Integrity of Localization Systems
    Elias Maharmeh, Zayed Alsayed, Fawzi Nashashibi · 2025 · Sensors
  19. Machine learning-based estimation of soil organic carbon in Thailand’s cash crops using multispectral and SAR data fusion combined with environmental variables
    Sunantha Ousaha, Zhenfeng Shao, Phodee Pattama, Potchara Ariyasakul, Xiao Huang, Afzal Zeeshan · 2025 · Geo-spatial Information Science
  20. Machine learning guidelines for designing next-generation nanocomposite membranes for CO 2 capture
    Doaa Sallam, Basamat S. Shaheen, Nageh K. Allam · 2025 · Green Chemistry
  21. Uncertainty Quantification for In Silico Chemistry
    Tom Frömbgen, Elizaveta Surzhikova, Jürgen Dölz, Jonny Proppe, Barbara Kirchner, Christoph R. Jacob · 2026 · Chemical Reviews
  22. Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population
    Bjarne Kerber, Tobias Hepp, Thomas Küstner, Sergios Gatidis · 2023 · PLoS ONE
  23. Towards Evidential and Class Separable Open Set Object Detection
    Ruofan Wang, Rui-Wei Zhao, Xiaobo Zhang, Rui Feng · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
  24. Ensemble Predictors: Possibilistic Combination of Conformal Predictors for Multivariate Time Series Classification
    Andrea Campagner, Marília Barandas, Duarte Folgado, Hugo Filipe Silveira Gamboa, Federico Cabitza · 2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence
  25. Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group
    Ismaïl Baaj, Zied Bouraoui, Antoine Cornuéjols, Thierry Denœux, Sébastien Destercke, Didier Dubois A, Marie‐Jeanne Lesot, João P. Marques-Silva, Jérôme Mengin, Henri M. Prade et al. · 2024 · International Journal of Approximate Reasoning
  26. Leveraging Viscous Hamilton–Jacobi PDEs for Uncertainty Quantification in Scientific Machine Learning
    Zongren Zou, Tingwei Meng, Paula X. Chen, Jérôme Darbon, George Em Karniadakis · 2024 · SIAM/ASA Journal on Uncertainty Quantification
  27. An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks
    Gaetan De Waele, Gerben Menschaert, Willem Waegeman · 2024 · eLife
  28. Empowering Bayesian Neural Networks with Functional Priors through Anchored Ensembling for Mechanics Surrogate Modeling Applications
    Javad Ghorbanian, Nicholas Casaprima, Audrey Olivier · 2024 · Computer Methods in Applied Mechanics and Engineering
  29. Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment
    Ebrahimpourboura Zahra, Manish Mosalpuri, Jonas Baltrušaitis, Pallavi Dubey, Mark Mba Wright · 2025 · Sustainability Science and Technology
  30. Outlier-detection for reactive machine learned potential energy surfaces
    Luis Itza Vazquez-Salazar, Silvan Käser, Markus Meuwly · 2025 · npj Computational Materials
  31. Quantification of aleatoric and epistemic uncertainty in Data-Driven occupant behavior model for building performance simulation
    Sunghyun Kim, Cheol Soo Park · 2025 · Energy and Buildings
  32. Applications of Deep Learning in Electromagnetics: Teaching Maxwell's equations to machines
    Roberto Miorelli, Anastassios Skarlatos, Caroline Vienne, Christophe Reboud, Pierre Calmon · 2022 · Institution of Engineering and Technology eBooks
  33. Chained Gaussian processes to estimate battery health degradation with uncertainties
    Benjamin Larvaron, Marianne Clausel, Antoine Bertoncello, Sébastien Benjamin, Georges Oppenheim · 2023 · Journal of Energy Storage
  34. Downscaling daily wind speed with Bayesian deep learning for climate monitoring
    Firas Gerges, Michel C. Boufadel, Elie R. Bou-Zeid, Hani H. Nassif, Jason T. L. Wang · 2023 · International Journal of Data Science and Analytics
  35. Histogram matching‐enhanced adversarial learning for unsupervised domain adaptation in medical image segmentation
    Xiaoxue Qian, Hua‐Chieh Shao, Yunxiang Li, Weiguo Lu, You Zhang · 2025 · Medical Physics
  36. Quantifying and managing uncertainty in systems biology: Mechanistic and data-driven models
    Eva Balsa‐Canto, Núria Campo-Manzanares, Artai R. Moimenta, Geoffrey Roudaut, Diego Troitiño-Jordedo · 2025 · Current Opinion in Systems Biology
  37. Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market
    Kerstin J.F. von Borries, Katie V. Beckwith, Jonathan M. Goodman, Weihsueh A. Chiu, Olivier Jolliet, Peter Fantke · 2026 · Nature Communications
  38. Machine learning for water quality prediction and uncertainty assessment
    Tarekegn Dejen Mengistu, Il-Moon Chung, Sun Woo Chang · 2026 · Physics and Chemistry of the Earth Parts A/B/C
  39. Epistemic and aleatoric uncertainty in optical vegetation trait retrieval: Concepts, Methods, and Outlook
    Jochem Verrelst, José Luis García-Soria, Pablo Reyes-Muñoz, Emma De Clerck, Miguel Morata, Juan Pablo Rivera-Caicedo · 2026 · ISPRS Journal of Photogrammetry and Remote Sensing
  40. Deep ensemble–based probabilistic modeling of torsional capacity in reinforced concrete beams with uncertainty decomposition
    Nguyen-Vu Luat, Hung La, Tan Nguyen · 2026 · Applied Mathematical Modelling
  41. Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification
    Jakob Gawlikowski, Sudipan Saha, Julia Niebling, Xiao Xiang Zhu · 2023 · EURASIP Journal on Advances in Signal Processing
  42. A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions
    Norman Knyazev, Harrie Oosterhuis · 2023 · ACM Conference on Recommender Systems (RecSys)
  43. Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm
    Ashleigh Ledger, Jolien Ceusters, Lil Valentin, Antonia Carla Testa, Caroline Van Holsbeke, Dorella Franchi, Tom Bourne, Wouter Froyman, Dirk Timmerman, Ben VAN CALSTER · 2023 · BMC Medical Research Methodology
  44. In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning
    Sebastian Schieferdecker, Florian Rottach, Esther Vock · 2024 · Journal of Chemical Information and Modeling
  45. Uncertainty Quantification of Data-driven Quality Prediction Model For Realizing the Active Sampling Inspection of Mechanical Properties in Steel Production
    Yong Hui Song, Feifei Li, Zheng Wang, Baozhong Zhang, Borui Zhang · 2024 · International Journal of Computational Intelligence Systems
  46. Integrating imprecise data in generative models using interval-valued Variational Autoencoders
    Luciano Sánchez, Nahuel Costa, Inés Couso, Olivier Strauss · 2024 · Information Fusion
  47. Attention-based multi-fidelity machine learning model for fractional flow reserve assessment
    Haizhou Yang, Brahmajee K. Nallamothu, Carlos Alberto Figueroa, Krishna Garikipati · 2024 · Computer Methods in Applied Mechanics and Engineering
  48. Advances in weather and climate extreme studies: a systematic comparative review
    Kamil Muhammad Kafi, Zakiah Ponrahono · 2024 · Discover Geoscience
  49. Using the Constrained Disorder Principle to Navigate Uncertainties in Biology and Medicine: Refining Fuzzy Algorithms
    Yaron Ilan · 2024 · Biology
  50. Uncertainty-Aware Time Series Anomaly Detection
    Paul Wiessner, Grigor Bezirganyan, Sana Sellami, Richard Chbeir, Hans‐Joachim Bungartz · 2024 · Future Internet
  51. Risk-aware classification via uncertainty quantification
    Murat Şensoy, Lance Kaplan, Simon Julier, Maryam Saleki, Federico Cerutti · 2024 · Expert Systems with Applications
  52. Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout
    Nijat Mehdiyev, Maxim Majlatow, Peter Fettke · 2024 · Data & Knowledge Engineering
  53. Shedding light on uncertainties in machine learning: formal derivation and optimal model selection
    Giulio Del Corso, Sara Colantonio, Claudia Caudai · 2025 · Journal of the Franklin Institute
  54. Towards reliable land cover mapping under domain shift: An overview and comprehensive comparative study on uncertainty estimation
    Chao Ji, Hong Tang · 2025 · Earth-Science Reviews
  55. Consistency-based diagnosis using data-driven residuals and limited training data
    Arman Mohammadi, Mattias Krysander, Daniel Jung · 2025 · Control Engineering Practice
  56. Assessment of uncertainty quantification in universal differential equations
    Nina Schmid, David Fernandes del Pozo, Willem Waegeman, Jan Hasenauer · 2025 · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  57. A Deep Learning Model for Chemical Shieldings in Molecular Organic Solids Including Anisotropy
    Matthias Kellner, Jacob Brian Holmes, Ruben Rodriguez-Madrid, Florian Viscosi, Yuxuan Zhang, Lyndon Emsley, Michele Ceriotti · 2025 · The Journal of Physical Chemistry Letters
  58. Attenuation Coefficient Estimation for PET/MRI With Bayesian Deep Learning Pseudo-CT and Maximum-Likelihood Estimation of Activity and Attenuation
    Andrew P. Leynes, Sangtae Ahn, Kristen A. Wangerin, Sandeep S. Kaushik, Florian Wiesinger, Thomas A. Hope, Peder E. Z. Larson · 2021 · IEEE Transactions on Radiation and Plasma Medical Sciences
  59. Accounting for Model Uncertainty in Algorithmic Discrimination
    Junaid Ali, Preethi Lahoti, Krishna P. Gummadi · 2021 · Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  60. The Evaluation of Uncertainty in Measurements Using Artificial Neural Network Techniques
    Marco Carratù, Vincenzo Gallo, Valter Laino, Consolatina Liguori, Vincenzo Paciello, Antonio Pietrosanto · 2023 · Annual Conference of the IEEE Industrial Electronics Society (IECON)
  61. A General Framework for Distributed Inference With Uncertain Models
    James Z. Hare, César A. Uribe, Lance Kaplan, Ali Jadbabaie · 2021 · IEEE Transactions on Signal and Information Processing over Networks
  62. Closeness and uncertainty aware adversarial examples detection in adversarial machine learning
    Ömer Faruk Tuna, Ferhat Özgür Çatak, M. Taner Eskil · 2022 · Computers & Electrical Engineering
  63. Evidential Reasoning and Learning: a Survey
    Federico Cerutti, Lance Kaplan, Murat Şensoy · 2022 · International Joint Conference on Artificial Intelligence
  64. Quantifying Epistemic Uncertainty in Deep Learning
    Ziyi Huang, Henry Lam, Haofeng Zhang · 2021 · arXiv (Cornell University)
  65. Quantum Computing for Climate Change Detection, Climate Modeling, and Climate Digital Twin
    Soronzonbold Otgonbaatar, Olli Nurmi, Mikael P. Johansson, Jarmo Mäkelä, tadeusz kocman, Piotr Gawron, Zbigniew Puchała, Jakub Mielzcarek, Artur Miroszewski, Corneliu Octavian Dumitru · 2023
  66. Evaluation of the random forest regression machine learning technique as an alternative to ecoregional based regression taper modelling
    Maria J. Diamantopoulou, Ramazan Özçelík, Şerife Kalkanlı Genç · 2025 · Computers and Electronics in Agriculture
  67. COMPARISON OF UNCERTAINTY QUANTIFICATION METHODS FOR CNN-BASED REGRESSION
    Kira Wursthorn, Markus Hillemann, Markus Ulrich · 2022 · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
  68. Mining and reasoning of data uncertainty-induced imprecision in deep image classification
    Zuowei Zhang, Liangbo Ning, Zechao Liu, Qingyu Yang, Weiping Ding · 2023 · Information Fusion
  69. Integrating Uncertainty Into Neural Network-Based Speech Enhancement
    Huajian Fang, Dennis Becker, Stefan Wermter, Timo Gerkmann · 2023 · IEEE/ACM Transactions on Audio Speech and Language Processing
  70. Improving domain generalization by hybrid domain attention and localized maximum sensitivity
    Wing W. Y. Ng, Qin Zhang, Cankun Zhong, Cankun Zhong · 2023 · Neural Networks
  71. Analytical Uncertainty Propagation in Neural Networks
    Paul Jungmann, Julia Poray, Akash S. Kumar · 2024 · IEEE Transactions on Neural Networks and Learning Systems
  72. Improving robustness in strategic energy planning: A novel decision support method to deal with epistemic uncertainties
    Antonio Francisco Rodríguez Matas, Pedro Linares, Manuel Pérez Bravo, José Carlos Romero · 2024 · Energy
  73. A survey on LED Prognostics and Health Management and uncertainty reduction
    Roberto Rocchetta, Elisa Perrone, Alexander Herzog, Pierre Dersin, A. Di Bucchianico · 2024 · Microelectronics Reliability
  74. Trustworthy Artificial Intelligence in the Context of Metrology
    Tameem Adel, Samuel Bilson, Mark Levene A, Andrew Thompson · 2024 · Studies in computational intelligence
  75. Real time adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural network proportional-integral-derivative controller for nonlinear systems
    A. Aziz Khater, Eslam M Gaballah, Mohammad El-Bardin, Ahmad M. El-Nagar · 2024 · ISA Transactions
  76. Zoom2Net: Constrained Network Telemetry Imputation
    Fengchen Gong, Divya Raghunathan, Aarti Gupta, Maria Apostolaki · 2024 · ACM SIGCOMM Conference (SIGCOMM)
  77. Meta transfer evidence deep learning for trustworthy few-shot classification
    Tong Liu, Chaoyu Wen, Qiangwei Xiong, Jin Li · 2024 · Expert Systems with Applications
  78. Advancing EEG prediction with deep learning and uncertainty estimation
    Mats Tveter, Thomas Tveitstøl, Christoffer Hatlestad‐Hall, Ana S Pérez T, Erik Taubøll, Anis Yazidi, Hugo L. Hammer, Ira Haraldsen · 2024 · Brain Informatics
  79. Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
    Farhad Pourkamali‐Anaraki, Jamal F. Husseini, Scott Edward Stapleton · 2024 · IEEE Access
  80. Adversarial Attack Detection Approach for Intrusion Detection Systems
    Elif Değirmenci, İlker Özçelik, Ahmet Taylan Yazıcı · 2024 · IEEE Access
  81. Uncertainty CNNs: A path to enhanced medical image classification performance
    Vasileios Ε. Papageorgiou, Γεώργιος Πετμεζάς, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras · 2025 · Mathematical Biosciences & Engineering
  82. Laser-induced breakdown spectroscopy combined with multi-task convolutional neural network for analyzing Sm, Nd, and Gd elements in uranium polymetallic ore
    Zhuo Wu, Jian Wu, Xinyu Guo, Huihui Zhu, Yubo Zhang, Xiaohui Su, Fuli Chen, Minghui Li, Runhui Wang, Keyi Xu et al. · 2025 · Spectrochimica Acta Part B Atomic Spectroscopy
  83. A new approach for product reliability prediction by considering the production factory lifecycle information
    Shashi Bhushan Gunjan, D.S. Srinivasu, Ramesh Babu N · 2025 · Reliability Engineering & System Safety
  84. Uncertainty-guided Bayesian active learning for cost-effective fault diagnosis with minimal labeled data
    Yuejian Chen, Liang Zhao, Te Han · 2025 · Engineering Applications of Artificial Intelligence
  85. Hybrid Process Models in Electrochemical Syntheses under Deep Uncertainty
    Fenila Francis-Xavier, Fabian Kubannek, René Schenkendorf · 2021 · Processes
  86. Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty
    Christoph Jansen, Hannah Blocher, Thomas Augustin, Georg Schollmeyer · 2022 · International Journal of Approximate Reasoning
  87. Sharing taxonomic expertise between natural history collections using image recognition
    Michael Greeff, Max Caspers, Vincent J. Kalkman, Luc Willemse, Barry Sunderland, Olaf Bánki, Laurens Hogeweg · 2022 · Research Ideas and Outcomes
  88. Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression
    Dongting Hu, Liuhua Peng, Tingjin Chu, Xiaoxing Zhang, Yinian Mao, Howard D. Bondell, Mingming Gong · 2022 · Lecture notes in computer science
  89. One Step Closer to Unbiased Aleatoric Uncertainty Estimation
    Zhang Wang, Ziwen Martin, Subhro Das, Tsui-Wei Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
  90. Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation
    Oliver Mey, André Felipe Schneider, Olaf Enge‐Rosenblatt, Yesnier Bravo, Pit Stenzel · 2021 · International Conference on Power Science and Engineering (ICPSE)
  91. On the Integration of Fundamental Knowledge about Degradation Processes into Data-Driven Diagnostics and Prognostics Using Theory-Guided Data Science
    Simon Hagmeyer, Peter Zeiler, Marco F. Huber · 2022 · PHM Society European Conference
  92. Confidence Evaluation for Machine Learning Schemes in Vehicular Sensor Networks
    Xinhu Zheng, Sijiang Li, Yuru Li, Dongliang Duan, Liuqing Yang, Xiang Cheng · 2022 · IEEE Transactions on Wireless Communications
  93. Interpretable Uncertainty Quantification in AI for HEP
    Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, M. Kagan, B. Nord, Nesar Ramachandra · 2022
  94. Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology
    MacDonald, Samual, Foley, Helena, Yap, Melvyn, Johnston, Rebecca L., Steven, Kaiah, Koufariotis, Lambros T., Sharma, Sowmya, Wood, Scott, Addala, Venkateswar, Pearson, John V. et al. · 2023 · Scientific Reports
  95. Artificial Intelligence and the ethics of navigating ambiguity
    SJ Bennett · 2025 · Big Data & Society
  96. A State‐Of‐The‐Art Survey of Remote Photoplethysmography for Contactless Health Parameters Sensing
    Shadman Sakib, Zahid Hasan, Nirmalya Roy · 2025 · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
  97. Fast Uncertainty Quantification by Sparse Data Learning From Multiphysics Systems
    Bozhao Sun, Yiyao Wang, Haoqiang Feng, Eric T. Chung, Wen-Yan Yin, Qiwei Zhan · 2023 · IEEE Transactions on Microwave Theory and Techniques
  98. Uncertainty Quantification for Text Classification
    Dell Zhang, Murat Şensoy, Masoud Makrehchi, Bilyana Taneva-Popova, Lin Gui, Yulan He · 2023 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
  99. Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
    Dennis Ulmer, Jes Frellsen, Christian Hardmeier · 2022 · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)
  100. DEED: DEep Evidential Doctor
    Awais Ashfaq, Markus Lingman, Murat Şensoy, Sławomir Nowaczyk · 2023 · Artificial Intelligence