From FUnction-based TO MOdel-based automated probabilistic reasoning for DEep Learning

Weighted Automata Extraction and Explanation of Recurrent Neural Networks for Natural Language Tasks

Autori: Zeming Wei, Xiyue Zhang, Yihao Zhang, Meng Sun
Pubblicato in: Journal of Logical and Algebraic Methods in Programming, Numero Volume 136, January 2024, 100907, 2023, ISSN 2352-2208
Editore: ELSEVIER
DOI: 10.1016/j.jlamp.2023.100907

Planning for Automated Vehicles with Human Trust

Autori: Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John Lenneman, David Parker, Lu Feng
Pubblicato in: ACM Transactions on Cyber-Physical Systems, 2022, ISSN 2378-962X
Editore: Association for Computing Machinery
DOI: 10.1145/3561059

Automated Verification of Concurrent Stochastic Systems

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Formal Methods in System Design, 2021, ISSN 0925-9856
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10703-020-00356-y

Evaluation and learning in two-player symmetric games via best and better response

Autori: Rui Yan, Weixian Zhang, Ruiliang Deng, Xiaoming Duan, Zongying Shi, Yisheng Zhong
Pubblicato in: Information Sciences, 2023, ISSN 0020-0255
Editore: Elsevier BV
DOI: 10.1016/j.ins.2023.119459

Physiologically-Informed Gaussian Processes for Interpretable Modelling of Psycho-Physiological States

Autori: Shadi Ghiasi, Andrea Patane, Luca Laurenti, Claudio Gentili, Enzo Pasquale Scilingo, Alberto Greco, Marta Kwiatkowska
Pubblicato in: EEE Journal of Biomedical and Health Informatics (J-BHI), 2022, ISSN 2168-2194
Editore: Institute of Electrical and Electronics Engineers Inc.

Multiplayer Homicidal Chauffeur Reach-Avoid Games: A Pursuit Enclosure Function Approach

Autori: Rui Yan, Xiaoming Duan, Rui Zou, Xin He, Zongying Shi, Francesco Bullo
Pubblicato in: Automatica, 2024, ISSN 1873-2836
Editore: Elsevier
DOI: 10.48550/arxiv.2311.02389

PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks

Autori: Xiyue Zhang, Benjie Wang, Marta Kwiatkowska, Huan Zhang
Pubblicato in: Journal of Machine Learning Research (JMLR), 2025, ISSN 1533-7928
Editore: JMLR
DOI: 10.48550/arxiv.2408.09262

Online control synthesis for uncertain systems under signal temporal logic specifications

Autori: Pian Yu, Yulong Gao, Frank J. Jiang, Karl H. Johansson and Dimos V. Dimarogonas
Pubblicato in: International Journal of Robotics Research, 2023, ISSN 0278-3649
Editore: SAGE Publications
DOI: 10.1177/02783649231212572

A Language for Modeling and Optimizing Experimental Biological Protocols

Autori: Luca Cardelli; Marta Kwiatkowska; Luca Laurenti
Pubblicato in: Computation, Numero 9, 107, 2021, ISSN 2079-3197
Editore: MDPI
DOI: 10.3390/computation9100107

On the Hardness of Robust Classification

Autori: Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska and James Worrell
Pubblicato in: Journal of Machine Learning Research, 2021, ISSN 1532-4435
Editore: MIT Press

Probabilistic Reach-Avoid for Bayesian Neural Networks

Autori: Wicker, Matthew; Laurenti, Luca; Patane, Andrea; Paoletti, Nicola; Abate, Alessandro; Kwiatkowska, Marta
Pubblicato in: Artificial Intelligence, Numero 8, 2024, ISSN 0004-3702
Editore: Elsevier BV
DOI: 10.48550/arxiv.2310.01951

Probabilistic model checking and autonomy

Autori: Marta Kwiatkowska, Gethin Norman and David Parker
Pubblicato in: Annual Review of Control, Robotics, and Autonomous Systems, Numero 5:1,, 2022, Pagina/e 385-410, ISSN 2573-5144
Editore: Annual Review of Control, Robotics, and Autonomous Systems
DOI: 10.1146/annurev-control-042820-010947

Adversarial Robustness Guarantees for Gaussian Processes

Autori: Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska
Pubblicato in: Journal of Machine Learning Research, Numero 23(146), 2022, Pagina/e 1−55, ISSN 2640-3498
Editore: PMLR

Robust Control for Dynamical Systems with Non-Gaussian Noise via Formal Abstractions.

Autori: Thom Badings, Licio Romao, Alessandro Abate, David Parker, Hasan A. Poonawala, Marielle Stoelinga and Nils Jansen.
Pubblicato in: Journal of Artificial Intelligence Research, Numero 76, 2023, ISSN 1076-9757
Editore: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.14253

Strategy Synthesis for Zero-Sum Neuro-Symbolic Concurrent Stochastic Games

Autori: Rui Yan, Gabriel Santos, Gethin Norman, David Parker, Marta Kwiatkowska
Pubblicato in: Information and Computation, 2024, Pagina/e 105193, ISSN 0890-5401
Editore: Academic Press
DOI: 10.1016/j.ic.2024.105193

A Framework for Simultaneous Task Allocation and Planning under Uncertainty

Autori: Fatma Faruq, Bruno Lacerda, Nick Hawes, David Parker
Pubblicato in: ACM Transactions on Autonomous and Adaptive Systems, 2024, ISSN 1556-4703
Editore: Association for Computing Machinery
DOI: 10.1145/3665499

Rational verification: game-theoretic verification of multi-agent systems

Autori: Abate, Alessandro; Gutierrez, Julian; Hammond, Lewis; Harrenstein, Paul; Kwiatkowska, Marta; Najib, Muhammad; Perelli, Giuseppe; Steeples, Thomas; Wooldridge, Michael
Pubblicato in: Applied Intelligence, Numero 51, 2021, Pagina/e 6569–6584, ISSN 0924-669X
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10489-021-02658-y

On the Role of Explainability and Uncertainty in Ensuring Safety of AI Applications

Autori: Rhiannon Falconmore
Pubblicato in: PhD thesis, 2022
Editore: University of Oxford

Automatic Verification and Strategy Synthesis for Zero-sum and Equilibria Properties of Concurrent Stochastic Games

Autori: Gabriel Santos
Pubblicato in: PhD thesis, 2021
Editore: University of Oxford

Formal Verification of Deep Reinforcement Learning Agents

Autori: Edoardo Bacci
Pubblicato in: PhD thesis, 2022
Editore: University of Birmingham

Sample complexity of robust learning against evasion attacks

Autori: Pascale Gourdeau
Pubblicato in: PhD thesis, 2023
Editore: University of Oxford

Tractable probabilistic models for causal learning and reasoning

Autori: Benjie Wang
Pubblicato in: PhD thesis, 2023
Editore: University of Oxford
DOI: 10.5287/ora-2anj4dbdx

Modelling Human-Like Decision Making and Social Trust Using Probabilistic Programming

Autori: Maciej Olejnik
Pubblicato in: PhD thesis, 2022
Editore: University of Oxford

On the Adversarial Robustness of Gaussian Processes

Autori: Andrea Patane
Pubblicato in: PhD thesis, 2021
Editore: University of Oxford

Robustness Evaluation of Deep Neural Networks with Provable Guarantees

Autori: Min Wu
Pubblicato in: PhD thesis, 2020
Editore: University of Oxford

On Robustness for Natural Language Processing

Autori: Emanuele La Malfa
Pubblicato in: PhD thesis, 2023
Editore: University of Oxford
DOI: 10.5287/ora-2a4grvayz

Adversarial robustness of Bayesian neural networks

Autori: Matthew Wicker
Pubblicato in: PhD thesis, 2022
Editore: University of Oxford

PRISM 4.8

Autori: David Parker, Gethin Norman, Marta Kwiatkowska
Pubblicato in: Software, 2023
Editore: n/a

On the Benefits of Invariance in Neural Networks

Autori: Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, Benjamin Bloem-Reddy
Pubblicato in: Technical report Presented as poster at the NeurIPS 2019 Machine Learning with Guarantees Workshop., 2020
Editore: Machine Learning
DOI: 10.48550/arxiv.2005.00178

Emergent Linguistic Structures in Neural Networks are Fragile

Autori: Emanuele La Malfa, Matthew Wicker, Marta Kwiatkowska
Pubblicato in: Technical report, 2023
Editore: arxiv
DOI: 10.48550/arxiv.2210.17406

PREMAP

Autori: Xiyue Zhang
Pubblicato in: Software, 2025
Editore: n/a

Model-Based Diagnosis with Multiple Observations: A Unified Approach for C Software and Boolean Circuits

Autori: Pedro Orvalho, Marta Kwiatkowska, Mikoláš Janota, Vasco Manquinho
Pubblicato in: 2025
Editore: arxiv

Bayesian Network Models of Causal Interventions in Healthcare Decision Making: Literature Review and Software Evaluation

Autori: Artem Velikzhanin, Benjie Wang, Marta Kwiatkowska
Pubblicato in: Technical report, under submission, 2022
Editore: Department of Computer Science University of Oxford
DOI: 10.48550/arxiv.2211.15258

Robustness of Unsupervised Representation Learning without Labels

Autori: Aleksandar Petrov, Marta Kwiatkowska
Pubblicato in: Technical report, under submission, 2022
Editore: online

PRISM-games 3.0 and 3.1

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Software, 2020
Editore: n/a

DeepBayes

Autori: Matthew Wicker
Pubblicato in: Software, 2022
Editore: n/a

Point-based Value Iteration for Neuro-Symbolic POMDPs

Autori: Rui Yan, Gabriel Santos, Gethin Norman, David Parker, Marta Kwiatkowska
Pubblicato in: Technical report, under submission, 2023
Editore: Technical report arXiv:2306.17639, arXiv.
DOI: 10.48550/arxiv.2306.17639

SafeDRL

Autori: David Parker
Pubblicato in: Software, 2022
Editore: n/a

PRISM-games 3.2

Autori: David Parker, Gethin Norman, Marta Kwiatkowska
Pubblicato in: Software, 2023
Editore: n/a

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks

Autori: Jon Vadillo, Roberto Santana, Jose A. Lozano, Marta Kwiatkowska
Pubblicato in: Technical report, under submission, 2024
Editore: TBC
DOI: 10.48550/arxiv.2403.13740

Uncertify: Attacks Against Neural Network Certification

Autori: Lorenz, Tobias; Kwiatkowska, Marta; Fritz, Mario
Pubblicato in: Technical report, under submission, Numero 1, 2021
Editore: Technical report - Under submission
DOI: 10.48550/arxiv.2108.11299

Double Machine Learning for Conditional Moment Restrictions: IV regression, Proximal Causal Learning and Beyond

Autori: Daqian Shao, Ashkan Soleymani, Francesco Quinzan, Marta Kwiatkowska
Pubblicato in: 2025
Editore: TBC
DOI: 10.48550/arxiv.2506.14950focustolearnmore

PRISM 4.7

Autori: David Parker, Gethin Norman, Marta Kwiatkowska
Pubblicato in: Software, 2021
Editore: n/a

PRISM 4.9

Autori: David Parker
Pubblicato in: Software, 2025
Editore: n/a

Human-in-the-Loop Oversight of AI is Compromised by Political Preferences

Autori: Terence Daniel Dores Cruz, Christopher Starke, Tim Katzke, Emmanuel Müller, Marta Kwiatkowska, Orly Lobel, Nils Köbis and Shaul Shalvi
Pubblicato in: 2025
Editore: PsyArXiv

Exact Verification of Graph Neural Networks with Incremental Constraint Solving

Autori: Minghao Liu, Chia-Hsuan Lu, Marta Kwiatkowska
Pubblicato in: 2025
Editore: TBC - Technical paper under submission
DOI: 10.48550/arxiv.2508.09320

STR-Cert: Robustness Certification for Deep Text Recognition on Deep Learning Pipelines and Vision Transformers

Autori: Daqian Shao, Lukas Fesser, Marta Kwiatkowska
Pubblicato in: Technical report, under submission, 2024
Editore: Technical report, under submission
DOI: 10.48550/arxiv.2401.05338

Learning Algorithms for Verification of Markov Decision Processes

Autori: Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelik, Vojtěch Forejt, Jan Křetínský, Marta Kwiatkowska, Tobias Meggendorfer, David Parker, Mateusz Ujma
Pubblicato in: Technical report, under submission, 2024
Editore: TBC

PRISM-games 3.2.1

Autori: David Parker
Pubblicato in: Software, 2025
Editore: n/a

Efficient Preimage Approximation for Neural Network Certification

Autori: Anton Björklund, Mykola Zaitsev, Marta Kwiatkowska
Pubblicato in: Technical paper, under submission, 2025
Editore: TBC
DOI: 10.48550/arxiv.2505.22798

Are Large Language Models Robust in UnderstandingCode Against Semantics-Preserving Mutations?

Autori: Pedro Orvalho, Marta Kwiatkowska
Pubblicato in: Technical paper under submission, 2025
Editore: TBC
DOI: 10.48550/arxiv.2505.10443

webppl-cognitive-agents

Autori: Maciej Olejnik
Pubblicato in: Software and data, 2022
Editore: n/a

PyVeritas: On Verifying Python via LLM-Based Transpilation and Bounded Model Checking for C

Autori: Pedro Orvalho, Marta Kwiatkowska
Pubblicato in: 2025
Editore: Technical report, pending to be accepted

The Complexity of Learning Temporal Properties

Autori: Benjamin Bordais, Daniel Neider, Rajarshi Roy
Pubblicato in: 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025), 2025
Editore: TBC

Bayesian Inference with Certifiable Adversarial Robustness

Autori: Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska
Pubblicato in: Proceedings, International Conference on Artificial Intelligence and Statistics (AISTATS'21), 2021
Editore: PMLR

Safe POMDP Online Planning via Shielding

Autori: Shili Sheng, David Parker, Lu Feng
Pubblicato in: In Proc. IEEE International Conference on Robotics and Automation (ICRA'24), 2024
Editore: The final version is forthcoming from IEEE.
DOI: 10.48550/arxiv.2309.10216

Learning Provably Robust Policies in Uncertain Parametric Environments

Autori: Yannik Schnitzer, Alessandro Abate, David Parker
Pubblicato in: In Proc. 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS'25), 2025
Editore: Springer Nature

Multi-Objective Controller Synthesis with Uncertain Human Preferences

Autori: Shenghui Chen, Kayla Boggess, David Parker, Lu Feng
Pubblicato in: Proc. ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS'22), 2022
Editore: ACM/IEEE International Conference on Cyber-Physical Systems
DOI: 10.48550/arxiv.2105.04662

Distributional Probabilistic Model Checking

Autori: Ingy Elsayed-Aly, David Parker, Lu Feng
Pubblicato in: In Proc. 16th International Symposium NASA Formal Methods (NFM'24), 2024, ISSN 0302-9743
Editore: Springer
DOI: 10.48550/arxiv.2309.05584

Learning Decision Policies with Instrumental Variables through Double Machine Learning.

Autori: Daqian Shao, Ashkan Soleymani, Francesco Quinzan, Marta Kwiatkowska
Pubblicato in: 41st. International Conference on Machine Learning (ICML 2024), 2024
Editore: TBC
DOI: 10.48550/arxiv.2405.08498

Learning Probabilistic Temporal Logic Specifications for Stochastic Systems

Autori: Rajarshi Roy, Yash Pote, David Parker, Marta Kwiatkowska
Pubblicato in: Proceedings of IJCAI-25, 2025
Editore: IJCAI-25

Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise

Autori: Thom S. Badings, Alessandro Abate, Nils Jansen, David Parker, Hasan A. Poonawala, Marielle Stoelinga
Pubblicato in: Proc. 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022
Editore: AAAI Press
DOI: 10.48550/arxiv.2110.12662

Strategyproof Reinforcement Learning from Human Feedback

Autori: Thomas Kleine Buening, Jiarui Gan, Debmalya Mandal, Marta Kwiatkowska
Pubblicato in: Proc. 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25), 2025
Editore: NeurIPS
DOI: 10.48550/arxiv.2503.09561focustolearnmore

The King is Naked: on the Notion of Robustness for Natural Language Processing

Autori: Emanuele La Malfa, Marta Kwiatkowska
Pubblicato in: Proc. 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022
Editore: Association for the Advancement of Artificial Intelligence
DOI: 10.48550/arxiv.2112.07605

Compositional Probabilistic and Causal Inference using Tractable Circuit Models

Autori: Benjie Wang, Marta Kwiatkowska
Pubblicato in: 26th International Conference on Artificial Intelligence and Statistics, AISTATS'23, Numero 206, 2023, Pagina/e 9488-9498, ISSN 2640-3498
Editore: Journal of Machine Learning Research
DOI: 10.48550/arxiv.2304.08278

FAST: Boosting Uncertainty-based Test Prioritization Methods for Neural Networks via Feature Selection

Autori: Jialuo Chen, Jingyi Wang, Xiyue Zhang, Youcheng Sun, Marta Kwiatkowska, Jiming Chen, Peng Cheng
Pubblicato in: 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024), 2024, Pagina/e https://conf.researchr.org/home/ase-2024
Editore: TBC
DOI: 10.48550/arxiv.2409.09130

Robustness Guarantees for Bayesian Neural Networks (invited extended abstract of a keynote speaker)

Autori: Marta Kwiatkowska
Pubblicato in: In Proc. 19th International Conference on Quantitative Evaluation of SysTems (QEST 2022), 2022
Editore: Springer

A Unifying Framework for Causal Imitation Learningwith Hidden Confounders

Autori: Daqian Shao, Thomas Kleine Buening, Marta Kwiatkowska.
Pubblicato in: Workshop on Spurious Correlation and Shortcut Learning: Foundations and Solutions, Workshop at The International Conference on Learning Representations (ICLR) 2025, 2025
Editore: OpenReview
DOI: 10.48550/arxiv.2502.07656

FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks

Autori: Tobias Lorenz, Marta Kwiatkowska, Mario Fritz
Pubblicato in: The German Conference on Pattern Recognition (GCPR), 2024, Pagina/e https://www.gcpr-vmv.de/year/2024
Editore: Springer Nature
DOI: 10.48550/arxiv.2406.11522

Planning with Linear Temporal Logic Specifications: Handling Quantifiable and Unquantifiable Uncertainty

Autori: Pian Yu, Yong Li, David Parker, Marta Kwiatkowska
Pubblicato in: Proc. at IEEE International Conference on Robotics and Automation (ICRA), 2025
Editore: TBC

Provable Preimage Under-Approximation for Neural Networks

Autori: Zhang, Xiyue; Wang, Benjie; Kwiatkowska, Marta
Pubblicato in: TACAS 2024, 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Numero 30, 2024, ISSN 0302-9743
Editore: Springer
DOI: 10.48550/arxiv.2305.03686

What Is Formal Verification Without Specifications? A Survey on Mining LTL Specifications

Autori: Daniel Neider, Rajarshi Roy
Pubblicato in: In: Jansen, N., et al. Principles of Verification: Cycling the Probabilistic Landscape . Lecture Notes in Computer Science, vol 15262, 2024
Editore: Springer
DOI: 10.48550/arxiv.2501.16274

Safe POMDP Online Planning among Dynamic Agents via Adaptive Conformal Prediction

Autori: Shili Sheng, Pian Yu, David Parker, Marta Kwiatkowska and Lu Feng
Pubblicato in: The IEEE Robotics and Automation Letters (RA-L), 2024
Editore: The IEEE Robotics and Automation Letters (RA-L)
DOI: 10.48550/arxiv.2404.15557

When to trust AI: advances and challenges for certification of neural networks

Autori: Marta Kwiatkowska, Xiyue Zhang
Pubblicato in: Proceedings of the 18th Conference on Computer Science and Intelligence Systems (FedCSIS 2023), 2023
Editore: IEEE

Symbolic Causal Inference via Operations on Probabilistic Circuits

Autori: Benjie Wang, Marta Kwiatkowska
Pubblicato in: NeurIPS Workshop on Neuro Causal and Symbolic AI (nCSI), 2022
Editore: NeurIPS

Robustness Guarantees for Credal Bayesian Networks via Constraint Relaxation over Probabilistic Circuits.

Autori: Hjalmar Wijk, Benjie Wang, Marta Kwiatkowska
Pubblicato in: Proc. 31st International Joint Conference on Artificial Intelligence (IJCAI'22), 2022
Editore: International Joint Conferences on Artificial Intelligence
DOI: 10.48550/arxiv.2205.05793

Robust Decision Pipelines: Opportunities and Challenges for AI in Business Process Modelling

Autori: Marta Kwiatkowska
Pubblicato in: BPM 2023 Forum, Utrecht, The Netherlands, 2023
Editore: A Springer Nature Computer Science book series.

Adversarial Robustness Certification for Bayesian Neural Networks

Autori: Matthew Wicker, Andrea Patane, Luca Laurenti, Marta Kwiatkowska
Pubblicato in: 6th International Symposium on Formal Methods (FM'24 invited paper), 2024
Editore: Springer
DOI: 10.48550/arxiv.2306.13614

Individual Fairness Guarantees for Neural Networks

Autori: Elias Benussi, Andrea Patane, Matthew Wicker, Luca Laurenti, Marta Kwiatkowska
Pubblicato in: Proc. 31st International Joint Conference on Artificial Intelligence (IJCAI'22), 2022
Editore: International Joint Conferences on Artificial Intelligence
DOI: 10.48550/arxiv.2205.05763

Expectation vs. Reality: Towards Verification of Psychological Games

Autori: Marta Kwiatkowska, Gethin Norman, David Parker and Gabriel Santos
Pubblicato in: In Jansen, N., et al., Principles of Verification: Cycling the Probabilistic Landscape, volume 15262 of LNCS, 2024, Pagina/e 126–154
Editore: Springer
DOI: 10.1007/978-3-031-75783-9

Certification of Iterative Predictions in Bayesian Neural Networks

Autori: Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska
Pubblicato in: 37th Conference on Uncertainty in Artificial Intelligence (UAI'21), 2021
Editore: Association for Uncertainty in Artificial Intelligence (AUAI)

Safety and Robustness for Deep Learning with Provable Guarantees

Autori: Marta Kwiatkowska
Pubblicato in: Proceedings, 35th IEEE/ACM International Conference on Automated Software Engineering (ASE ’20), 2020
Editore: ACM

Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization

Autori: Pedro Orvalho, Mikola´s Janota, Vasco Manquinho
Pubblicato in: Proc. Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), 2024
Editore: TBC
DOI: 10.48550/arxiv.2502.07786

Sample Efficient Model-free Reinforcement Learning from LTL Specifications with Optimality Guarantees

Autori: Daqian Shao, Marta Kwiatkowska
Pubblicato in: 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Numero n/a, 2023
Editore: IJCAI
DOI: 10.24963/ijcai.2023/465

Sample complexity bounds for robustly learning decision lists against evasion attacks

Autori: Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska and James Worrell
Pubblicato in: Proc. 31st International Joint Conference on Artificial Intelligence (IJCAI'22), 2022
Editore: International Joint Conferences on Artificial Intelligence
DOI: 10.48550/arxiv.2205.06127

HSVI-based Online Minimax Strategies for Partially Observable Stochastic Games with Neural Perception Mechanisms

Autori: Rui Yan, Gabriel Santos, Gethin Norman, David Parker, Marta Kwiatkowska
Pubblicato in: Proc. 6th Annual Learning for Dynamics & Control Conference, L4DC 2024, 2024
Editore: 6th Annual Learning for Dynamics & Control Conference, L4DC 2024
DOI: 10.48550/arxiv.2404.10679focustolearnmore

Probabilistic Model Checking for Strategic Equilibria-based Decision Making: Advances and Challenges.

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos, Rui Yan
Pubblicato in: In Proc. 47th International Symposium on Mathematical Foundations of Computer Science (MFCS'22)., Numero 241 (4), 2022
Editore: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
DOI: 10.4230/lipics.mfcs.2022.4

Verified Probabilistic Policies for Deep Reinforcement Learning

Autori: Edoardo Bacci, David Parker
Pubblicato in: International Symposium NASA Formal Methods (NFM'22)., 2022
Editore: Springer
DOI: 10.48550/arxiv.2201.03698

When are Local Queries Useful for Robust Learning?https://papers.nips.cc/paper_files/paper/2022/hash/db6461eaf0eaeaad1d9c4a70e4818cbd-Abstract-Conference.html

Autori: Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
Pubblicato in: NeurIPS 2022, 2022
Editore: NeurIPS paper

Finite-horizon Equilibria for Neuro-symbolic Concurrent Stochastic Games

Autori: Rui Yan, Gabriel Santos, Xiaoming Duan, David Parker, Marta Kwiatkowska
Pubblicato in: Proc. 38th Conference on Uncertainty in Artificial Intelligence (UAI'22), 2022
Editore: AUAI Press

Certifiers Make Neural Networks Vulnerable to Availability Attacks

Autori: Tobias Lorenz, Marta Kwiatkowska and Mario Fritz
Pubblicato in: 16th ACM Workshop on Artificial Intelligence and Security (AISec 2023), 2023
Editore: AISec 2023

Probabilistic Guarantees for Safe Deep Reinforcement Learning

Autori: Edoardo Bacci, David Parker
Pubblicato in: Formal Modeling and Analysis of Timed Systems - 18th International Conference, FORMATS 2020, Vienna, Austria, September 1–3, 2020, Proceedings, Numero 12288, 2020, Pagina/e 231-248, ISBN 978-3-030-57627-1
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-57628-8_14

DRCFS: Doubly Robust Causal Feature Selection

Autori: Francesco Quinzan, Ashkan Soleymani, Patrik Jaillet, Cristian R. Rojas, Stefan Bauer
Pubblicato in: Fortieth International Conference on Machine Learning, ICML 2023, 2023
Editore: ICML 2023

Multi-player Equilibria Verification for Concurrent Stochastic Games

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Proc. 17th International Conference on Quantitative Evaluation of SysTems (QEST'20), 2020
Editore: Springer

On Correctness, Precision, and Performance in Quantitative Verification: QComp 2020 Competition Report

Autori: Carlos E. Budde, Arnd Hartmanns, Michaela Klauck, Jan Kretinsky, David Parker, Tim Quatmann, Andrea Turrini and Zhen Zhang
Pubblicato in: Proc. 9th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (ISoLA'20), 2020
Editore: Springer

Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks

Autori: Matthias König, Xiyue Zhang, Holger H. Hoos, Marta Kwiatkowska, Jan N. van Rijn
Pubblicato in: ECML-PKDD 2024- European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2024, 2024
Editore: TBC
DOI: 10.48550/arxiv.2406.10154

Robust anytime learning of Markov decision processes

Autori: Marnix Suilen, Thiago D. Simão, Nils Jansen, David Parker
Pubblicato in: In Proc. 36th Annual Conference on Neural Information Processing Systems (NeurIPS'22), 2022
Editore: NeurIPS 2022
DOI: 10.48550/arxiv.2205.15827

MIBP-Cert: Certified Training against Data Perturbations with Mixed-Integer Bilinear Programs.

Autori: Tobias Lorenz, Marta Kwiatkowska and Mario Fritz
Pubblicato in: Proc. 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25), 2025
Editore: Curran Associates

Provable Guarantees on the Robustness of Decision Rules to Causal Interventions

Autori: Benjie Wang, Clare Lyle, Marta Kwiatkowska
Pubblicato in: 30th International Joint Conference on Artificial Intelligence (IJCAI'21), 2021
Editore: IJCAI

Tractable Uncertainty for Structure Learning

Autori: Benjie Wang, Matthew Wicker, Marta Kwiatkowska
Pubblicato in: Proc. 39th International Conference on Machine Learning (ICML'22), 2022
Editore: PMLR

The Trembling-Hand Problem for LTLf Planning

Autori: Pian Yu, Shufang Zhu, Giuseppe De Giacomo, Marta Kwiatkowska, Moshe Vardi
Pubblicato in: 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024), 2024
Editore: IJCAI 2024/TBC
DOI: 10.48550/arxiv.2404.16163

Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models

Autori: Hannah Rose Kirk, yennie jun, Filippo Volpin, Haider Iqbal, Elias Benussi, Frederic Dreyer, Aleksandar Shtedritski, Yuki Asano
Pubblicato in: Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021
Editore: PMLR

Safety Verification for Deep Neural Networks with Provable Guarantees (Invited Paper)

Autori: Marta Kwiatkowska
Pubblicato in: 30th International Conference on Concurrency Theory (CONCUR 2019), 2019
Editore: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
DOI: 10.4230/lipics.concur.2019.1

Safety Guarantees for Iterative Predictions with Gaussian Processes

Autori: Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen Roberts
Pubblicato in: Proceedings, 59th IEEE Conference on Decision and Control (CDC), 2020
Editore: IEEE

Robust Markov Decision Processes: A Place Where AI and Formal Methods Meet

Autori: Marnix Suilen, Thom Badings, Eline M. Bovy, David Parker, Nils Jansen
Pubblicato in: In Jansen, N., et al., Principles of Verification: Cycling the Probabilistic Landscape, volume 15262 of LNCS, 2024, Pagina/e 126–154
Editore: Springer
DOI: 10.48550/arxiv.2411.11451

Efficient Solution and Learning of Robust Factored MDPs

Autori: Yannik Schnitzer, Alessandro Abate, David Parker
Pubblicato in: Proc. 40th AAAI Conference on Artificial Intelligence (AAAI'26), 2026
Editore: AAAI

Partially Observable Stochastic Games with Neural Perception Mechanisms

Autori: Rui Yan, Gabriel Santos, Gethin Norman, David Parker, Marta Kwiatkowska
Pubblicato in: In Proc. 26th International Symposium on Formal Methods (FM'24), 2024
Editore: Springer
DOI: 10.48550/arxiv.2310.11566

PRISM-games 3.0: Stochastic Game Verification with Concurrency, Equilibria and Time

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21–24, 2020, Proceedings, Part II, Numero 12225, 2020, Pagina/e 475-487, ISBN 978-3-030-53290-1
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-53291-8_25

Assessing Robustness of Text Classification through Maximal Safe Radius Computation

Autori: Emanuele La Malfa, Min Wu, Luca Laurenti, Benjie Wang, Anthony Hartshorn, Marta Kwiatkowska
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2020, 2020, Pagina/e 2949-2968
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2020.findings-emnlp.266

Verifying Reinforcement Learning up to Infinity

Autori: Edoardo Bacci, Mirco Giacobbe, David Parker
Pubblicato in: Proceedings, 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021
Editore: IJCAI

Multi-agent verification and control with probabilistic model checking

Autori: David Parker
Pubblicato in: Proc. 20th International Conference on Quantitative Evaluation of SysTems (QEST'23), 2023, Pagina/e https://www.qest.org/qest2023/
Editore: Spinger
DOI: 10.48550/arxiv.2308.02829

Learning Dynamics and Generalization in Reinforcement Learning

Autori: Clare Lyle, Mark Rowland, Will Dabney, Marta Kwiatkowska, Yarin Gal
Pubblicato in: Proc. 39th International Conference on Machine Learning (ICML'22), 2022
Editore: PMLR

Correlated equilibria and fairness in concurrent stochastic games

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Tools and Algorithms for the Construction and Analysis of Systems - 28th International Conference, TACAS 2022, 2022, ISSN 0302-9743
Editore: Springer

On Guaranteed Optimal Robust Explanations for NLP Models

Autori: Emanuele La Malfa, Agnieszka Zbrzezny, Rhiannon Michelmore, Nicola Paoletti, Marta Kwiatkowska
Pubblicato in: Proceedings, 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021
Editore: IJCAI

Invariant Causal Prediction for Block MDPs

Autori: Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Pubblicato in: Proceedings of the 37th International Conference on Machine Learning (ICML), 2020
Editore: PMLR 119

Probabilistic Safety for Bayesian Neural Networks

Autori: Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska
Pubblicato in: Proceedings, 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020), 2020
Editore: PMLR

Strategy Synthesis for Partially Observable Stochastic Games with Neural Perception Mechanisms

Autori: Marta Kwiatkowska
Pubblicato in: 32nd EACSL Annual Conference on Computer Science Logic (CSL 2024), 2024
Editore: Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik
DOI: 10.4230/lipics.csl.2024.5

Tools at the Frontiers of Quantitative Verification

Autori: Roman Andriushchenko, Alexander Bork, Carlos E. Budde, Milan Češka, Kush Grover, Ernst Moritz Hahn, Arnd Hartmanns, Bryant Israelsen, Nils Jansen, Joshua Jeppson, Sebastian Junges, Maximilian A. Köhl, Bettina Könighofer, Jan Křetínský, Tobias Meggendorfer, David Parker, Stefan Pranger, Tim Quatmann, Enno Ruijters, Landon Taylor, Matthias Volk, Maximilian Weininger, Zhen Zhang
Pubblicato in: TOOLympics III, 2024
Editore: Springer
DOI: 10.48550/arxiv.2405.13583

Adversarial Robustness Guarantees for Classification with Gaussian Processes

Autori: Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen Roberts
Pubblicato in: Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS 2020), 2020
Editore: PMLR
DOI: 10.48550/arxiv.1905.11876

Probabilistic Timed ATL

Autori: Wojciech Jamroga, Marta Kwiatkowska, Wojciech Penczek, Laure Petrucci, Teofil Sidoruk
Pubblicato in: 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025, 2025
Editore: TBC

Reactive and human-in-the-loop planning and control of multi-robot systems under LTL specifications in dynamic environments

Autori: Pian Yu, Gianmarco Fedeli and Dimos V. Dimarogonas
Pubblicato in: 9th International Conference on Control, Decision and Information Technologies (CoDIT 2023), 2023
Editore: EEE Xplore
DOI: 10.48550/arxiv.2307.06000

Robustness Guarantees for Deep Neural Networks on Videos

Autori: Min Wu, Marta Kwiatkowska
Pubblicato in: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Pagina/e 308-317, ISBN 978-1-7281-7168-5
Editore: IEEE
DOI: 10.1109/cvpr42600.2020.00039

Tractable Uncertainty for Structure Learning

Autori: Benjie Wang, Matthew Wicker, Marta Kwiatkowska
Pubblicato in: In 5th Workshop on Tractable Probabilistic Modelling (TPM). This paper was accepted for ICML 2022, Numero 162, 2022, Pagina/e 23131-23150
Editore: PMLR

Trust-Aware Motion Planning for Human-Robot Collaboration under Distribution Temporal Logic Specifications

Autori: Yu, Pian; Dong, Shuyang; Sheng, Shili; Feng, Lu; Kwiatkowska, Marta
Pubblicato in: 2024 IEEE International Conference on Robotics and Automation (ICRA2024), 2024
Editore: IEEE
DOI: 10.48550/arxiv.2310.01163

Probabilistic Model Checking: Applications and Trends

Autori: Marta Kwiatkowska, Gethin Norman, David Parker
Pubblicato in: Lecture Notes in Computer Science, Principles of Formal Quantitative Analysis, 2025, Pagina/e 158-173
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-97439-7_7

Symbolic Verification and Strategy Synthesis for Turn-based Stochastic Games

Autori: Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos
Pubblicato in: Principles of Systems Design, Lecture Notes in Computer Science, 2022, Pagina/e 9783031223365, ISBN 978-3-031-22336-5
Editore: Springer
DOI: 10.1007/978-3-031-22337-2_19

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