On the safety of machine learning: Cyber-physical systems, decision sciences, and data products

Cited by (211)

Items 101–200 of 211

1. Safety Monitoring of Machine Learning Perception Functions: A Survey
   Raúl Ferreira, Joris Michel Guerin, Kévin Delmas, Jérémie Guiochet, Hélène Waeselynck · 2025 · Computational Intelligence
2. Evaluating Object (Mis)Detection From a Safety and Reliability Perspective: Discussion and Measures
   Andrea Ceccarelli, Leonardo Montecchi · 2023 · IEEE Access
3. Machine learning with requirements: A manifesto
   Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz · 2024 · Neurosymbolic Artificial Intelligence
4. Diverse explanations from data-driven and domain-driven perspectives in the physical sciences
   Sichao Li, Xin Wang, Amanda Susan Barnard · 2024 · Machine Learning Science and Technology
5. Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects
   Sampo Kuutti, Saber Fallah, Richard Bowden, Phil Barber · 2019 · Synthesis lectures on advances in automotive technology
6. An interpretable health behavioral intervention policy for mobile device users
   Xinyu Hu, P.-Y. S. Hsueh, C.-H. Chen, Keith M. Diaz, Faith Parsons, Ipek Ensari, Min Qian, Ying Kuen Cheung · 2018 · IBM Journal of Research and Development
7. Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study
   Anahid Jalali, Alexander Schindler, Bernhard Haslhofer, Andreas Rauber · 2020 · PHM Society European Conference
8. Decision Support Systems in HF based on Deep Learning Technologies
   Marco Penso, Sarah Solbiati, Sara Moccia, Enrico Gianluca Caiani · 2022 · Current Heart Failure Reports
9. Towards Knowledge Uncertainty Estimation for Open Set Recognition
   C.T.A. Pires, Marília Barandas, Letícia Fernandes, Duarte Folgado, Hugo Filipe Silveira Gamboa · 2020 · Machine Learning and Knowledge Extraction
10. Putting Safety of Intended Functionality SOTIF into Practice
    Amr Abdulazim, Moustafa Elbahaey, Abduallah Mohamed · 2021 · SAE technical papers on CD-ROM/SAE technical paper series
11. Safety in the Face of Unknown Unknowns: Algorithm Fusion in Data-driven Engineering Systems
    Nina Kshetry, Lav R. Varshney · 2019 · IEEE International Conference on Acoustics Speech and Signal Processing
12. Navigating Transparency: The Influence of On-demand Explanations on Non-expert User Interaction with AI
    Jörg Papenkordt · 2024 · Lecture notes in computer science
13. UTrack: Multi-object Tracking with Uncertain Detections
    E. Solano‐Carrillo, Felix Sattler, Antje Alex, Alexander Klein, Bruno Pereira Costa, Ángel Bueno Rodríguez, Jannis Stoppe · 2025 · Lecture notes in computer science
14. Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models
    Chiradeep Roy, Mahsan Nourani, Shivvrat Arya, Mahesh Shanbhag, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate · 2023 · ACM Transactions on Interactive Intelligent Systems
15. Path-Sampling and Machine Learning for Rare Abnormal Events: Application to Polymerization CSTRs
    Vikram Sudarshan, Warren D. Seider, Amish J. Patel, Ulku G. Oktem, Jeffrey E. Arbogast · 2024 · Chemical Engineering Science
16. Logic Programming and Machine Ethics
    Abeer Dyoub, Stefania Costantini, Francesca Alessandra Lisi · 2020 · Electronic Proceedings in Theoretical Computer Science
17. Combining white box models, black box machines and human interventions for interpretable decision strategies
    Grégory Gadzinski, Alessio Castello · 2022 · Judgment and Decision Making
18. Bridging the Gap between ISO 26262 and Machine Learning: A Survey of Techniques for Developing Confidence in Machine Learning Systems
    Jose Serna, Simon Diemert, Laure Millet, Rami Debouk, Ramesh S, Jeffrey J. Joyce · 2020 · SAE International Journal of Advances and Current Practices in Mobility
19. Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact
    Kush R. Varshney, Aleksandra Mojsilović · 2019 · arXiv (Cornell University)
20. A novel uncertainty-aware point cloud approach for geometric quality monitoring in construction
    Hanbin Luo, Jianjiang Zhan, Junxiao Liu, Wei Zhou, Weili Fang · 2025 · Advanced Engineering Informatics
21. Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies
    Sampo Kuutti, Saber Fallah, R. Bowden · 2020 · IEEE International Conference on Robotics and Automation
22. On Mismatched Detection and Safe, Trustworthy Machine Learning
    Kush R. Varshney · 2020 · Conference on Information Sciences and Systems
23. No, Not That Verification: Challenges Posed by Testing, Evaluation, Validation and Verification of Artificial Intelligence in Weapon Systems
    Maaike Verbruggen · 2022 · Studies in peace and security
24. Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings
    Utkarsh Sarawgi, Rishab Khincha, Wazeer Deen Zulfikar, Satrajit Ghosh, Pattie Maes · 2021 · International Joint Conference on Neural Networks (IJCNN)
25. Challenges and Directions for Ambient Intelligence: A Cyber Physical Systems Perspective
    John A. Stankovic, Meiyi Ma, Sarah Masud Preum, Homa Alemzadeh · 2021 · IEEE International Conference on Cognitive Machine Intelligence (CogMI)
26. Designing Fiduciary Artificial Intelligence
    Sebastian Benthall, David Shekman · 2023 · ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO)
27. A Comprehensive Technological Survey on Dependable Self-Managing CPS: The Decade of Researches on Correctness and Dependability
    Peng Zhou, Kun Mean Hou, Zhan Zhang, Decheng Zuo, Jian Dong, Jian‐Jin Li, Haiyin Zhou · 2017 · Preprints.org
28. Explainable AI in Data-Driven Finance: Balancing Algorithmic Transparency with Operational Optimization Demands
    Monisola Beauty Ayankoya · 2025 · International Journal of Research Publication and Reviews
29. Reliability Analysis of Architectural Safeguards for AI-enabled Systems
    Max Scheerer, Ralf Reussner · 2023 · IEEE International Conference on Engineering of Complex Computer Systems (ICECCS)
30. Internal and collective interpretation for improving human interpretability of multi-layered neural networks
    Ryotaro Kamimura · 2019 · International Journal of Advances in Intelligent Informatics
31. A Probabilistic Model Checking Approach to Self-adapting Machine Learning Systems
    Maria Casimiro, David Garlan, Javier Cámara, Luı́s Rodrigues, Paolo Romano · 2022 · Lecture notes in computer science
32. Bias Mitigation Post-processing for Individual and Group Fairness
    Pranay Lohia, Karthikeyan Natesan Ramamurthy, Manish A. Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri · 2018 · arXiv (Cornell University)
33. AI literacy for safe deployment: Cross-national evidence on the interaction between talent and governance
    Jeong-Ah Park, Chang Hyun Kim, Hye-jin Kim · 2025 · Telecommunications Policy
34. Dynamic Simplex: Balancing Safety and Performance in Autonomous Cyber Physical Systems
    Baiting Luo, Shreyas Ramakrishna, Ava Pettet, Christopher B. Kuhn, Gábor Karsai, Ayan Mukhopadhyay · 2023 · ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS)
35. ANN uncertainty estimates in assessing fatty liver content from ultrasound data
    Gianna M. Del Corso, Maria Antonietta Pascali, Claudia Caudai, Laura De Rosa, Antonio Salvati, Marcello Mancini, Lorenzo Ghiadoni, Ferruccio Bonino, Maurizia Rossana Brunetto, Sara Colantonio et al. · 2024 · Computational and Structural Biotechnology Journal
36. Mathematical Consistency and Long-Term Behaviour of a Dynamical System with a Self-Organising Vector Field
    Natalia Janson, Peter E. Kloeden · 2020 · Journal of Dynamics and Differential Equations
37. Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles
    Utkarsh Sarawgi, Wazeer Deen Zulfikar, Rishab Khincha, Pattie Maes · 2020 · arXiv (Cornell University)
38. A hybrid machine learning approach for housing price prediction: the stacking regressor method
    Ömer Gökberk Erbulut, Zeynep Çolak · 2025 · International Journal of Housing Markets and Analysis
39. Adaptive Risk Mitigation Strategies for Generative AI-Driven Threats
    Abdelraouf M. Ishtaiwi, Amjad Yousef Aldweesh, Ahmad Al–Qerem · 2025 · Advances in computational intelligence and robotics book series
40. Machine Learning in Government Applications: A Review
    Inder Pal Singh Sethi, Om Pradyumana Gupta, Ritesh Kumar Dwivedi, Misha Kapoor, Sulbha Bhaisare, Vijay Kumar Chaudhari, Shobhit Varma · 2025 · Procedia Computer Science
41. Cybersecurity in the Age of AI-Enhancing Defences for Today's Threats
    Rohini Vijay Tarade, Susanta Das · 2025 · IGI Global eBooks
42. Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks
    Ryotaro Kamimura, Haruhiko Takeuchi · 2019 · Connection Science
43. Promoting Distributed Trust in Machine Learning and Computational Simulation via a Blockchain Network
    Nelson Bore, Ravi Kiran Raman, Markus, Isaac M., Sekou L. Remy, Oliver Bent, Michael Hind, Eleftheria Kyriaki Pissadaki, Biplav Srivastava, Roman Vaculín, Kush R. Varshney et al. · 2018 · arXiv (Cornell University)
44. Automated Dependence Plots
    David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar · 2019 · arXiv (Cornell University)
45. Serverless on FHIR: Deploying machine learning models for healthcare on the cloud
    Bell Raj Eapen, Kamran Sartipi, Norm Archer · 2020 · arXiv (Cornell University)
46. Time integration and reject options for probabilistic output of pairwise LVQ
    Johannes Brinkrolf, Barbara Hammer · 2019 · Neural Computing and Applications
47. Inherently Safer Design Approaches and Improvement Strategies in Process Industries
    Baiju Karun, V. R. Renjith, M. Sudheep Elayidom · 2021 · International Conference on Smart Computing and Communications (ICSCC)
48. DocXplain: A Novel Model-Agnostic Explainability Method for Document Image Classification
    Saifullah Saifullah, Stefan Agne, Andreas R. Dengel, Sheraz Ahmed · 2024 · Lecture notes in computer science
49. Advancing clinical genomics: Bridging the gap between deep learning models and interpretability for improved decision support
    George Oche Ambrose, Olugbenga Ayodeji Mokuolu, Mohammed Baba Abdulkadir, Selimat Ibrahim, Itiolu Ibilola Funsho, Toluwani Mokuolu, Lukman Lawal · 2024 · Elsevier eBooks
50. Vehicle Motion Sickness Profiling Through Interpretable Gradient Boosting: A Framework for Advanced Driver Assistance Systems
    Jon Ander Ruiz Colmenares, Estibaliz Asua · 2025 · IEEE Access
51. Data Invariants: On Trust in Data-Driven Systems.
    Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani, Alexandra Meliou · 2020
52. A New Reinforcement Learning-Based Framework for Unbiased Autonomous Software Systems
    Ismail Abiodun Sulaimon, Ahmed Ghoneim, Mubarak Rashed Alrashoud · 2019 · International Conference on Modeling, Simulation, and Applied Optimization
53. Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors
    Beepul Bharti, Paul Hyunsoo Yi, Jeremias Sulam · 2022 · PubMed
54. Next Generation Trustworthy Fraud Detection
    Sihong Xie, Philip S. Yu · 2018 · IEEE International Conference on Collaboration and Internet Computing (CIC)
55. Prediction intervals for Deep Neural Networks
    Tullio Mancini, Hector Calvo-Pardo, José Olmo · 2020 · RePEc: Research Papers in Economics
56. Optimization Path for Management Decision-Making of Chinese Public Hospitals Under the Background of Big Data
    Qinqin Wu, Nur Ajrun Khalid · 2024 · Journal of Information Systems Engineering & Management
57. Energy-Efficient AI in Industrial Hazard Monitoring
    Subuhi Kashif Ansari, Abu Sarwar Zamani · 2026 · The Springer series in applied machine learning
58. Emerging Paradigms in AI, Autonomous Systems, and Intelligent Technologies: A Synthesis of the First Edition
    Liviu Marian Ungureanu, Iulian Sorin Munteanu · 2026 · Technologies
59. Capital and Value in Late Adulthood
    Robert J. Griffore · 2019 · Family and Consumer Sciences Research Journal
60. Bidirectional Estimation of Partially Black-Boxed Layers of SOM-Based Convolutional Neural Networks
    Ryotaro Kamimura · 2020 · Advances in intelligent systems and computing
61. Humans as Mitigators of Biases in Risk Prediction via Field Studies
    Bei Wang, Arul Mishra, Himanshu Mishra · 2022 · IEEE International Conference on Big Data (BigData)
62. Applications of AI Techniques in Health Care and Well-Being Systems
    P Shiridi Kumar, Rohit, Satyabrata Jena, Rajeev Shrivastava · 2024 · Lecture notes in networks and systems
63. Carving Out Control Code: Automated Identification of Control Software in Autopilot Systems
    Balaji Balasubramaniam, Iftekhar Ahmed, Hamid Bagheri, Justin M. Bradley · 2024 · ACM Transactions on Cyber-Physical Systems
64. Compressing and Interpreting SOM-Based Convolutional Neural Networks
    Ryotaro Kamimura · 2020 · Lecture notes in computer science
65. Selective Information Control and Network Compression in Multi-layered Neural Networks
    Ryotaro Kamimura · 2021 · Lecture notes in networks and systems
66. SOAR: Simultaneous Or‐of‐And Rules for classification of positive and negative classes
    Elena Khusainova, Emily Dodwell, Ritwik Mitra · 2023 · Stat
67. Machine Learning Safety: An Overview
    José Miguel Faria · 2018 · Safety-Critical Systems Symposium (SSS)
68. How an Electrical Engineer Became an Artificial Intelligence Researcher, a Multiphase Active Contours Analysis
    Kush R. Varshney · 2018 · arXiv (Cornell University)
69. Actionable Interpretation of Machine Learning Models for Sequential Data: Dementia-related Agitation Use Case
    Nutta Homdee, John Lach · 2020 · arXiv (Cornell University)
70. Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems
    Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani, Alexandra Meliou · 2020 · arXiv (Cornell University)
71. Epistemic uncertainty estimation for object detection in open-set conditions
    Dimity Miller · 2021 · Queensland University of Technology
72. Next-gen AI for Aerospace Engineering
    Samir Khan · 2025
73. Information-Theoretic Self-compression of Multi-layered Neural Networks
    Ryotaro Kamimura · 2018 · Lecture notes in computer science
74. Correlation-Constrained Mutual Information Maximization for Interpretable Multi-Layered Neural Networks
    Ryotaro Kamimura, Haruhiko Takeuchi · 2018 · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS)
75. Information Compression for Intelligible Multi-Layered Neural Networks
    Ryotaro Kamimura · 2019 · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
76. Cost-conscious mutual information maximization for improving collective interpretation of multi-layered neural networks
    Ryotaro Kamimura · 2020 · Neurocomputing
77. Connective Potential Information for Collectively Interpreting Multi-Layered Neural Networks
    Ryotaro Kamimura · 2020 · IEEE Symposium Series on Computational Intelligence (SSCI)
78. Disentangled Representations by Pseudo-Maximum Mutual Information for Interpreting Multi-Layered Neural Networks
    Ryotaro Kamimura · 2020 · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
79. Can a single neuron learn quantiles
    E. Solano‐Carrillo · 2021 · arXiv (Cornell University)
80. An Integrated Cybersecurity Risk Management (I-CSRM) Framework for Critical Infrastructure Protection
    Halima Ibrahim Kure · 2021 · UEL Research Repository (University of East London)
81. Multi-level selective potentiality maximization for interpreting multi-layered neural networks
    Ryotaro Kamimura · 2022 · Applied Intelligence
82. Interpretable GAM Models: Predicting Sepsis in ICU Patients
    Wai Kit Tsang, Dries F. Benoit · 2022 · Intelligent systems reference library
83. COMPARACIÓN EMPÍRICA DE DOS MODELOS DE APRENDIZAJE AUTOMÁTICO GENERADOS MEDIANTE PROCESOS DIFERENTES
    Alveiro Rosado Gómez, Liliana Calderón-Benavides, Jorge Andrick Parra Valencia · 2023 · REVISTA COLOMBIANA DE TECNOLOGIAS DE AVANZADA
84. ÖĞRETMEN ADAYLARINA YÖNELİK AKILLI TELEFONLARIN TASARIMINDA GÜVENLİK BEKLENTİLERİ ÖLÇEĞİNİN (ATTGBÖ) GELİŞTİRİLMESİ
    Süleyman Burak Tozkoparan, Ferhan Odabaşı, Adile Aşkım Kurt · 2023 · Mehmet Akif Ersoy üniversitesi eğitim fakültesi dergisi.
85. A Framework for Anticipating Structural Vulnerabilities in Ai-Enhanced Techno-Social Systems: The Case of Advanced Microgrids
    Alexandros Gazos, J. Kahn, Isabel Kusche, Christian Büscher, Markus Götz · 2023 · SSRN Electronic Journal
86. Adversarial examples detection based on ensembles of defenses and counter-attacks
    Rolan Alexander Valle Rey Sánchez · 2022
87. SPSS: A Salience-based Poisoning Selection Strategy for Selecting Backdoor Attack Victims
    Zihan Lyu, Dongheng Lin, Shengkai Sun, Jie Zhang, Ruiming Zhang · 2024 · International Joint Conference on Neural Networks (IJCNN)
88. Effective Continuous Quantitative Measures for End-to-End AI Guardrails
    Jason M. Pittman · 2024 · Proceedings of the International Conference on AI Research.
89. AI-Compass: A Framework For Identifying High-Impact AI Use Cases
    Anuj Kumar Gupta · 2025 · SSRN Electronic Journal
90. An Explainable Error Detection Approach for Machine Learning
    Kaixing Wu, Changwu Huang, Xin Yao · 2025 · Lecture notes in computer science
91. A Hybrid, Neuro-symbolic Approach for Scholarly Knowledge Organization
    Hassan Hussein, Allard Oelen, Sören Auer · 2025 · ACM Symposium on Document Engineering (DocEng)
92. EGA: Explainable Deep Belief Network-Based Autoencoder Using Novel Extended Garson Algorithm
    Satyam Kumar, Vadlamani Ravi · 2025 · Lecture notes in networks and systems
93. On the Philosophical Naivety of Engineers in the Age of Machine Learning
    Mohannad Zeyad Naser · 2025 · Topoi
94. From artificial to organic: Rethinking the roots of intelligence for digital health
    Prajwal Ghimire, Keyoumars Ashkan · 2025 · PLOS Digital Health
95. The Evolution of Ontology Merging: Historical Perspectives and Modern Approaches
    Naoual Smaili, Adil Kabbaj · 2025 · International Conference on Intelligent Systems: Theories and Applications
96. PAC Learning Or: Why We Should (and Shouldn't) Trust Machine Learning
    Dylan Cashman · 2025 · Journal of Visualization and Interaction
97. Data-Driven and Scenario-Based Risk Analysis Considering Uncertainty in Machine Learning Systems
    Toshiya Okubo, Hironori Washizaki, Naoyasu Ubayashi, Nobukazu Yoshioka, Hironori Takeuchi, Truong Vinh Truong Duy · 2026 · Lecture notes in computer science
98. Statistical learning with high-cardinality string categorical variables
    Patricio Cerda Reyes · 2019
99. A Neural-Symbolic learning framework to produce interpretable predictions for image classification
    Adrien Bennetot · 2022 · theses.fr (ABES)
100. Runtime safety monitoring of ML-based perception functions in autonomous systems
     Raúl Ferreira · 2023 · theses.fr (ABES)