Proof-Carrying Neuro-Symbolic Code. - Komendantskaya, Ekaterina (2025)

Neural Network Verification is a Programming Language Challenge. - Cordeiro, Lucas C.; Daggitt, Matthew L.; Girard-Satabin, Julien; Isac, Omri; Johnson, Taylor T.; Katz, Guy; Komendantskaya, Ekaterina; Lemesle, Augustin; Manino, Edoardo; Sinkarovs, Artjoms; Wu, Haoze (2025)

Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs (Invited Talk). - Daggitt, Matthew L.; Kokke, Wen; Atkey, Robert; Komendantskaya, Ekaterina; Slusarz, Natalia; Arnaboldi, Luca (2025)

Formally Verifying Robustness and Generalisation of Network Intrusion Detection Models. - Flood, Robert; Casadio, Marco; Aspinall, David; Komendantskaya, Ekaterina (2025)

Neural Network Verification is a Programming Language Challenge. - Cordeiro, Lucas C.; Daggitt, Matthew L.; Girard-Satabin, Julien; Isac, Omri; Johnson, Taylor T.; Katz, Guy; Komendantskaya, Ekaterina; Lemesle, Augustin; Manino, Edoardo; Sinkarovs, Artjoms; Wu, Haoze (CoRR, 2025)

Proof-Carrying Neuro-Symbolic Code. - Komendantskaya, Ekaterina (CoRR, 2025)

A Generalised Framework for Property-Driven Machine Learning. - Flinkow, Thomas; Casadio, Marco; Kessler, Colin; Monahan, Rosemary; Komendantskaya, Ekaterina (CoRR, 2025)

Neural Network Verification for Gliding Drone Control: A Case Study. - Kessler, Colin; Komendantskaya, Ekaterina; Casadio, Marco; Viola, Ignazio Maria; Flinkow, Thomas; Othman, Albaraa Ammar; Malhotra, Alistair; McPherson, Robbie (CoRR, 2025)

A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks. - Padalkar, Parth; Slusarz, Natalia; Komendantskaya, Ekaterina; Gupta, Gopal (Theory Pract. Log. Program., 2024)

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. - Wu, Haoze; Isac, Omri; Zeljic, Aleksandar; Tagomori, Teruhiro; Daggitt, Matthew L.; Kokke, Wen; Refaeli, Idan; Amir, Guy; Julian, Kyle; Bassan, Shahaf; Huang, Pei; Lahav, Ori; et al. (2024)

Generating Traffic-Level Adversarial Examples from Feature-Level Specifications. - Flood, Robert; Casadio, Marco; Aspinall, David; Komendantskaya, Ekaterina (2024)

A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks. - Padalkar, Parth; Slusarz, Natalia; Komendantskaya, Ekaterina; Gupta, Gopal (2024)

Taming Differentiable Logics with Coq Formalisation. - Affeldt, Reynald; Bruni, Alessandro; Komendantskaya, Ekaterina; Slusarz, Natalia; Stark, Kathrin (2024)

Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs. - Daggitt, Matthew L.; Kokke, Wen; Atkey, Robert; Slusarz, Natalia; Arnaboldi, Luca; Komendantskaya, Ekaterina (CoRR, 2024)

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. - Wu, Haoze; Isac, Omri; Zeljic, Aleksandar; Tagomori, Teruhiro; Daggitt, Matthew L.; Kokke, Wen; Refaeli, Idan; Amir, Guy; Julian, Kyle; Bassan, Shahaf; Huang, Pei; Lahav, Ori; et al. (CoRR, 2024)

NLP Verification: Towards a General Methodology for Certifying Robustness. - Casadio, Marco; Dinkar, Tanvi; Komendantskaya, Ekaterina; Arnaboldi, Luca; Isac, Omri; Daggitt, Matthew L.; Katz, Guy; Rieser, Verena; Lemon, Oliver (CoRR, 2024)

Taming Differentiable Logics with Coq Formalisation. - Affeldt, Reynald; Bruni, Alessandro; Komendantskaya, Ekaterina; Slusarz, Natalia; Stark, Kathrin (CoRR, 2024)

A Certified Proof Checker for Deep Neural Network Verification. - Desmartin, Remi; Isac, Omri; Komendantskaya, Ekaterina; Stark, Kathrin; Passmore, Grant O.; Katz, Guy (CoRR, 2024)

A Neurosymbolic Framework for Bias Correction in CNNs. - Padalkar, Parth; Slusarz, Natalia; Komendantskaya, Ekaterina; Gupta, Gopal (CoRR, 2024)

Neuro-Symbolic AI + Agent Systems: A First Reflection on Trends, Opportunities and Challenges. - Belle, Vaishak; Fisher, Michael; Russo, Alessandra; Komendantskaya, Ekaterina; Nottle, Alistair (2023)

The Vehicle Tutorial: Neural Network Verification with Vehicle. - Daggitt, Matthew L.; Kokke, Wen; Komendantskaya, Ekaterina; Atkey, Robert; Arnaboldi, Luca; Slusarz, Natalia; Casadio, Marco; Coke, Ben; Lee, Jeonghyeon (2023)

ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. - Casadio, Marco; Arnaboldi, Luca; Daggitt, Matthew L.; Isac, Omri; Dinkar, Tanvi; Kienitz, Daniel; Rieser, Verena; Komendantskaya, Ekaterina (2023)

Compiling Higher-Order Specifications to SMT Solvers: How to Deal with Rejection Constructively. - Daggitt, Matthew L.; Atkey, Robert; Kokke, Wen; Komendantskaya, Ekaterina; Arnaboldi, Luca (2023)

Towards a Certified Proof Checker for Deep Neural Network Verification. - Desmartin, Remi; Isac, Omri; Passmore, Grant O.; Stark, Kathrin; Komendantskaya, Ekaterina; Katz, Guy (2023)

Logic of Differentiable Logics: Towards a Uniform Semantics of DL. - Slusarz, Natalia; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Stewart, Robert J.; Stark, Kathrin (2023)

Logic of Differentiable Logics: Towards a Uniform Semantics of DL. - Slusarz, Natalia; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Stewart, Robert J.; Stark, Kathrin (CoRR, 2023)

ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. - Casadio, Marco; Arnaboldi, Luca; Daggitt, Matthew L.; Isac, Omri; Dinkar, Tanvi; Kienitz, Daniel; Rieser, Verena; Komendantskaya, Ekaterina (CoRR, 2023)

Towards a Certified Proof Checker for Deep Neural Network Verification. - Desmartin, Remi; Isac, Omri; Passmore, Grant O.; Stark, Kathrin; Katz, Guy; Komendantskaya, Ekaterina (CoRR, 2023)

The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning. - Kienitz, Daniel; Komendantskaya, Ekaterina; Lones, Michael A. (2022)

Comparing Complexities of Decision Boundaries for Robust Training: A Universal Approach. - Kienitz, Daniel; Komendantskaya, Ekaterina; Lones, Michael A. (2022)

Differentiable Logics for Neural Network Training and Verification. - Slusarz, Natalia; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Stewart, Robert J. (2022)

Neural Networks in Imandra: Matrix Representation as a Verification Choice. - Desmartin, Remi; Passmore, Grant O.; Komendantskaya, Ekaterina (2022)

Neural Network Robustness as a Verification Property: A Principled Case Study. - Casadio, Marco; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Kokke, Wen; Katz, Guy; Amir, Guy; Refaeli, Idan (2022)

CheckINN: Wide Range Neural Network Verification in Imandra. - Desmartin, Remi; Passmore, Grant O.; Komendantskaya, Ekaterina; Daggitt, Matthew L. (2022)

Mathematics of Program Construction - 14th International Conference, MPC 2022, Tbilisi, Georgia, September 26-28, 2022, Proceedings (Springer, 2022)

Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers. - Daggitt, Matthew L.; Kokke, Wen; Atkey, Robert; Arnaboldi, Luca; Komendantskaya, Ekaterina (CoRR, 2022)

Neural Networks in Imandra: Matrix Representation as a Verification Choice. - Desmartin, Remi; Passmore, Grant O.; Komendantskaya, Ekaterina (CoRR, 2022)

Why Robust Natural Language Understanding is a Challenge. - Casadio, Marco; Komendantskaya, Ekaterina; Rieser, Verena; Daggitt, Matthew L.; Kienitz, Daniel; Arnaboldi, Luca; Kokke, Wen (CoRR, 2022)

Differentiable Logics for Neural Network Training and Verification. - Slusarz, Natalia; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Stewart, Robert J. (CoRR, 2022)

CheckINN: Wide Range Neural Network Verification in Imandra (Extended). - Desmartin, Remi; Passmore, Grant O.; Komendantskaya, Ekaterina; Daggitt, Matthew L. (CoRR, 2022)

Actions you can handle: dependent types for AI plans. - Hill, Alasdair; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Petrick, Ronald P. A. (2021)

Property-driven Training: All You (N)Ever Wanted to Know About. - Casadio, Marco; Daggitt, Matthew L.; Komendantskaya, Ekaterina; Kokke, Wen; Kienitz, Daniel; Stewart, Rob (CoRR, 2021)

Actions You Can Handle: Dependent Types for AI Plans. - Hill, Alasdair; Komendantskaya, Ekaterina; Daggitt, Matthew L.; Petrick, Ronald P. A. (CoRR, 2021)

The New Normal: We Cannot Eliminate Cuts in Coinductive Calculi, But We Can Explore Them. - Komendantskaya, Ekaterina; Rozplokhas, Dmitry; Basold, Henning (Theory Pract. Log. Program., 2020)

Neural Networks, Secure by Construction - An Exploration of Refinement Types. - Kokke, Wen; Komendantskaya, Ekaterina; Kienitz, Daniel; Atkey, Robert; Aspinall, David (2020)

Accuracy, Training Time and Hardware Efficiency Trade-Offs for Quantized Neural Networks on FPGAs. - Bacchus, Pascal; Stewart, Robert J.; Komendantskaya, Ekaterina (2020)

Relative Robustness of Quantized Neural Networks Against Adversarial Attacks. - Duncan, Kirsty; Komendantskaya, Ekaterina; Stewart, Robert J.; Lones, Michael A. (2020)

Continuous Verification of Machine Learning: a Declarative Programming Approach. - Komendantskaya, Ekaterina; Kokke, Wen; Kienitz, Daniel (2020)

Proof-Carrying Plans: a Resource Logic for AI Planning. - Hill, Alasdair; Komendantskaya, Ekaterina; Petrick, Ronald P. A. (2020)

Practical Aspects of Declarative Languages - 22nd International Symposium, PADL 2020, New Orleans, LA, USA, January 20-21, 2020, Proceedings (Springer, 2020)

The New Normal: We Cannot Eliminate Cuts in Coinductive Calculi, But We Can Explore Them. - Komendantskaya, Ekaterina; Rozplokhas, Dmitry; Basold, Henning (CoRR, 2020)

Proof-Carrying Plans: a Resource Logic for AI Planning. - Hill, Alasdair; Komendantskaya, Ekaterina; Petrick, Ronald P. A. (CoRR, 2020)

Coinduction in Uniform: Foundations for Corecursive Proof Search with Horn Clauses. - Basold, Henning; Komendantskaya, Ekaterina; Li, Yue (2019)

Proof-Carrying Plans. - Schwaab, Christopher; Komendantskaya, Ekaterina; Hill, Alasdair; Farka, Frantisek; Petrick, Ronald P. A.; Wells, Joe B.; Hammond, Kevin (2019)

Proceedings of the 21st International Symposium on Principles and Practice of Programming Languages, PPDP 2019, Porto, Portugal, October 7-9, 2019. (ACM, 2019)

Coinductive Uniform Proofs. - Komendantskaya, Ekaterina; Li, Yue (CoRR, 2019)

Neural Network Verification for the Masses (of AI graduates). - Komendantskaya, Ekaterina; Stewart, Rob; Duncan, Kirsty; Kienitz, Daniel; Hen, Pierre Le; Bacchus, Pascal (CoRR, 2019)

Logic programming: Laxness and saturation. - Komendantskaya, Ekaterina; Power, John (J. Log. Algebraic Methods Program., 2018)

Proof-relevant Horn Clauses for Dependent Type Inference and Term Synthesis. - Farka, Frantisek; Komendantskaya, Ekaterina; Hammond, Kevin (Theory Pract. Log. Program., 2018)

Towards Coinductive Theory Exploration in Horn Clause Logic: Position Paper. - Komendantskaya, Ekaterina; Li, Yue (2018)

Proof-relevant Horn Clauses for Dependent Type Inference and Term Synthesis. - Farka, Frantisek; Komendantskaya, Ekaterina; Hammond, Kevin (CoRR, 2018)

Coinduction in Uniform: Foundations for Corecursive Proof Search with Horn Clauses. - Basold, Henning; Komendantskaya, Ekaterina; Li, Yue (CoRR, 2018)

Operational semantics of resolution and productivity in Horn clause logic. - Fu, Peng; Komendantskaya, Ekaterina (Formal Aspects Comput., 2017)

Productive corecursion in logic programming. - Komendantskaya, Ekaterina; Li, Yue (Theory Pract. Log. Program., 2017)

Proof Mining with Dependent Types. - Komendantskaya, Ekaterina; Heras, Jónathan (2017)

Proceedings of the First Workshop on Coalgebra, Horn Clause Logic Programming and Types, CoALP-Ty 2016, Edinburgh, UK, 28-29 November 2016. (2017)

Proof Mining with Dependent Types. - Komendantskaya, Ekaterina; Heras, Jónathan (CoRR, 2017)

Productive Corecursion in Logic Programming. - Komendantskaya, Ekaterina; Li, Yue (CoRR, 2017)

Coalgebraic logic programming: from Semantics to Implementation. - Komendantskaya, Ekaterina; Power, John; Schmidt, Martin (J. Log. Comput., 2016)

Category Theoretic Semantics for Theorem Proving in Logic Programming: Embracing the Laxness. - Komendantskaya, Ekaterina; Power, John (2016)

Proof Relevant Corecursive Resolution. - Fu, Peng; Komendantskaya, Ekaterina; Schrijvers, Tom; Pond, Andrew (2016)

A Productivity Checker for Logic Programming. - Komendantskaya, Ekaterina; Johann, Patricia; Schmidt, Martin (2016)

Coinductive Soundness of Corecursive Type Class Resolution. - Farka, Frantisek; Komendantskaya, Ekaterina; Hammond, Kevin (2016)

Structural Resolution for Abstract Compilation of Object-Oriented Languages. - Franceschini, Luca; Ancona, Davide; Komendantskaya, Ekaterina (2016)

Category theoretic semantics for theorem proving in logic programming: embracing the laxness. - Komendantskaya, Ekaterina; Power, John (CoRR, 2016)

Operational Semantics of Resolution in Horn Clause Logic. - Fu, Peng; Komendantskaya, Ekaterina (CoRR, 2016)

A Productivity Checker for Logic Programming. - Komendantskaya, Ekaterina; Johann, Patricia; Schmidt, Martin (CoRR, 2016)

Coinductive Soundness of Corecursive Type Class Resolution. - Farka, Frantisek; Komendantskaya, Ekaterina; Hammond, Kevin; Fu, Peng (CoRR, 2016)

Logic programming: laxness and saturation. - Komendantskaya, Ekaterina; Power, John (CoRR, 2016)

CoALP-Ty'16. - Komendantskaya, Ekaterina; Farka, Frantisek (CoRR, 2016)

Structural Resolution for Logic Programming. - Johann, Patricia; Komendantskaya, Ekaterina; Komendantskiy, Vladimir (2015)

A Type-Theoretic Approach to Resolution. - Fu, Peng; Komendantskaya, Ekaterina (2015)

A Type-Theoretic Approach to Structural Resolution. - Fu, Peng; Komendantskaya, Ekaterina (CoRR, 2015)

Structural Resolution for Logic Programming. - Johann, Patricia; Komendantskaya, Ekaterina; Komendantskiy, Vladimir (CoRR, 2015)

A Type-Theoretic Approach to Resolution. - Fu, Peng; Komendantskaya, Ekaterina (CoRR, 2015)

Structural Resolution: a Framework for Coinductive Proof Search and Proof Construction in Horn Clause Logic. - Komendantskaya, Ekaterina; Johann, Patricia (CoRR, 2015)

Proof Relevant Corecursive Resolution. - Fu, Peng; Komendantskaya, Ekaterina; Schrijvers, Tom; Pond, Andrew (CoRR, 2015)

Recycling Proof Patterns in Coq: Case Studies. - Heras, Jónathan; Komendantskaya, Ekaterina (Math. Comput. Sci., 2014)

ACL2(ml): Machine-Learning for ACL2. - Heras, Jónathan; Komendantskaya, Ekaterina (2014)

Proof Pattern Search in Coq/SSReflect. - Heras, Jónathan; Komendantskaya, Ekaterina (CoRR, 2014)

Guarding (Co)Recursion in Coalgebraic Logic Programming. - Heras, Jónathan; Komendantskaya, Ekaterina; Schmidt, Martin (CoRR, 2014)

HoTT formalisation in Coq: Dependency Graphs & ML4PG. - Heras, Jónathan; Komendantskaya, Ekaterina (CoRR, 2014)

Proof-Pattern Recognition and Lemma Discovery in ACL2. - Heras, Jónathan; Komendantskaya, Ekaterina; Johansson, Moa; Maclean, Ewen (2013)

ML4PG in Computer Algebra Verification. - Heras, Jónathan; Komendantskaya, Ekaterina (2013)

Exploiting Parallelism in Coalgebraic Logic Programming. - Komendantskaya, Ekaterina; Schmidt, Martin; Heras, Jónathan (2013)

Statistical Proof-Patterns in Coq/SSReflect - Heras, Jónathan; Komendantskaya, Ekaterina (CoRR, 2013)

ML4PG: proof-mining in Coq - Heras, Jónathan; Komendantskaya, Ekaterina (CoRR, 2013)

Statistical Proof Pattern Recognition: Automated or Interactive? - Heras, Jónathan; Komendantskaya, Ekaterina (CoRR, 2013)

Proof-Pattern Recognition in ACL2. - Heras, Jónathan; Komendantskaya, Ekaterina; Johansson, Moa; Maclean, Ewen (CoRR, 2013)

Exploiting Parallelism in Coalgebraic Logic Programming. - Komendantskaya, Ekaterina; Schmidt, Martin; Heras, Jónathan (CoRR, 2013)

Coalgebraic Logic Programming: from Semantics to Implementation. - Komendantskaya, Ekaterina; Power, John; Schmidt, Martin (CoRR, 2013)

Neural Networks for Proof-Pattern Recognition. - Komendantskaya, Ekaterina; Lichota, Kacper (2012)

Machine Learning in Proof General: Interfacing Interfaces - Komendantskaya, Ekaterina; Heras, Jónathan; Grov, Gudmund (2012)

Partiality and Recursion in Interactive Theorem Provers, PAR@ITP 2010, Edinburgh, UK, July 15, 2010 (EasyChair, 2012)

Unification neural networks: unification by error-correction learning. - Komendantskaya, Ekaterina (Log. J. IGPL, 2011)

Coalgebraic Semantics for Derivations in Logic Programming. - Komendantskaya, Ekaterina; Power, John (2011)

Coalgebraic Derivations in Logic Programming. - Komendantskaya, Ekaterina; Power, John (2011)

Machine Learning Coalgebraic Proofs. - Komendantskaya, Ekaterina (2011)

SHERLOCK - An Interface for Neuro-Symbolic Networks. - Komendantskaya, Ekaterina; Zhang, Qiming (2011)

Coalgebraic Semantics for Parallel Derivation Strategies in Logic Programming. - Komendantskaya, Ekaterina; McCusker, Guy; Power, John (2010)

Neuro-symbolic Representation of Logic Programs Defining Infinite Sets. - Komendantskaya, Ekaterina; Broda, Krysia; Garcez, Artur S. d'Avila (2010)

Proceedings Workshop on Partiality and Recursion in Interactive Theorem Provers, PAR 2010, Edinburgh, UK, 15th July 2010. (2010)

Parallel Rewriting in Neural Networks. - Komendantskaya, Ekaterina (2009)

Neurons or Symbols - Why does OR Remain Exclusive?. - Komendantskaya, Ekaterina (2009)

Using Structural Recursion for Corecursion - Bertot, Yves; Komendantskaya, Ekaterina (CoRR, 2009)

Fibrational Semantics for Many-Valued Logic Programs: Grounds for Non-Groundness. - Komendantskaya, Ekaterina; Power, John (2008)

Unification by Error-Correction. - Komendantskaya, Ekaterina (2008)

Using Structural Recursion for Corecursion. - Bertot, Yves; Komendantskaya, Ekaterina (2008)

Inductive and Coinductive Components of Corecursive Functions in Coq. - Bertot, Yves; Komendantskaya, Ekaterina (2008)

Inductive and Coinductive Components of Corecursive Functions in Coq - Bertot, Yves; Komendantskaya, Ekaterina (CoRR, 2008)

First-order deduction in neural networks. - Komendantskaya, Ekaterina (2007)

A Sequent Calculus for Bilattice-Based Logic and Its Many-Sorted Representation. - Komendantskaya, Ekaterina (2007)

Connectionist Representation of Multi-Valued Logic Programs. - Komendantskaya, Ekaterina; Lane, Máire; Seda, Anthony Karel (2007)

Sound and Complete SLD-Resolution for Bilattice-Based Annotated Logic Programs. - Komendantskaya, Ekaterina; Seda, Anthony Karel (2006)