Vaishak Belle

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 118

Top Venues

RWTH Aachen University (PHD)

Education History

RWTH Aachen University

PHD

Publications

Weizhi Tang, Vaishak Belle
ToM-LM: Delegating Theory of Mind Reasoning to External Symbolic Executors in Large Language Models. CoRR (2024)
Weizhi Tang, Vaishak Belle
Zero, Finite, and Infinite Belief History of Theory of Mind Reasoning in Large Language Models. CoRR (2024)
Miguel Ángel Méndez Lucero, Enrique Bojorquez Gallardo, Vaishak Belle
Semantic Objective Functions: A distribution-aware method for adding logical constraints in deep learning. CoRR (2024)
Daxin Liu, Vaishak Belle
Progression with Probabilities in the Situation Calculus: Representation and Succinctness. AAMAS (2024)
Ioannis Papantonis, Vaishak Belle
Principled diverse counterfactuals in multilinear models. Mach. Learn. 113 (3) (2024)
Andreas C. Bueff, Vaishak Belle
Learning explanatory logical rules in non-linear domains: a neuro-symbolic approach. Mach. Learn. 113 (7) (2024)
Weizhi Tang, Vaishak Belle
LTLBench: Towards Benchmarks for Evaluating Temporal Logic Reasoning in Large Language Models. CoRR (2024)
Andreas Bueff, Vaishak Belle
Logic + Reinforcement Learning + Deep Learning: A Survey. ICAART (3) (2023)
Till Hofmann, Vaishak Belle
Abstracting Noisy Robot Programs. AAMAS (2023)
Daxin Liu, Qihui Feng, Vaishak Belle, Gerhard Lakemeyer
Concerning Measures in a First-order Logic with Actions and Meta-beliefs. KR (2023)
Vaishak Belle
Toward A Logical Theory Of Fairness and Bias. CoRR (2023)
Vaishak Belle, Thomas Bolander, Andreas Herzig, Bernhard Nebel
Epistemic planning: Perspectives on the special issue. Artif. Intell. 316 (2023)
Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. Theory Pract. Log. Program. 23 (4) (2023)
Ioannis Papantonis, Vaishak Belle
Model Transparency: Why Do We Care? ICAART (3) (2023)
Paulius Dilkas, Vaishak Belle
Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures. KR (2023)
Qihui Feng, Daxin Liu, Vaishak Belle, Gerhard Lakemeyer
A Logic of Only-Believing over Arbitrary Probability Distributions. AAMAS (2023)
Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. CoRR (2023)
Andreas Bueff, Vaishak Belle
Deep Inductive Logic Programming meets Reinforcement Learning. CoRR (2023)
Vaishak Belle
Excursions in First-Order Logic and Probability: Infinitely Many Random Variables, Continuous Distributions, Recursive Programs and Beyond. JELIA (2023)
Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. AAMAS (2023)
Ionela G. Mocanu, Vaishak Belle
Knowledge representation and acquisition in the era of large language models: Reflections on learning to reason via PAC-Semantics. Nat. Lang. Process. J. 5 (2023)
Sandrine Chausson, Ameer Saadat-Yazdi, Xue Li, Jeff Z. Pan, Vaishak Belle, Nadin Kökciyan, Björn Ross
A Web-based Tool for Detecting Argument Validity and Novelty. AAMAS (2023)
Ioannis Papantonis, Vaishak Belle
Why not both? Complementing explanations with uncertainty, and the role of self-confidence in Human-AI collaboration. CoRR (2023)
Vaishak Belle
Knowledge representation and acquisition for ethical AI: challenges and opportunities. Ethics Inf. Technol. 25 (1) (2023)
Paulius Dilkas, Vaishak Belle
Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures. CoRR (2023)
Bénédicte Legastelois, Amy Rafferty, Paul Brennan, Hana Chockler, Ajitha Rajan, Vaishak Belle
Challenges in Explaining Brain Tumor Detection. TAS (2023)
Vaishak Belle
Statistical relational learning and neuro-symbolic AI: what does first-order logic offer? CoRR (2023)
Drew Hemment, Matjaz Vidmar, Daga Panas, Dave Murray-Rust, Vaishak Belle, Ruth Aylett
Agency and legibility for artists through Experiential AI. CoRR (2023)
Ioannis Papantonis, Vaishak Belle
Transparency in Sum-Product Network Decompilation. ECAI (2023)
Daxin Liu, Qinfei Huang, Vaishak Belle, Gerhard Lakemeyer
Verifying Belief-Based Programs via Symbolic Dynamic Programming. ECAI (2023)
Vaishak Belle
Actions, Continuous Distributions and Meta-Beliefs. AAMAS (2023)
Drew Hemment, Dave Murray-Rust, Vaishak Belle, Ruth Aylett, Matjaz Vidmar, Frank Broz
Experiential AI: A transdisciplinary framework for legibility and agency in AI. CoRR (2023)
Vaishak Belle, Michael Fisher, Alessandra Russo, Ekaterina Komendantskaya, Alistair Nottle
Neuro-Symbolic AI + Agent Systems: A First Reflection on Trends, Opportunities and Challenges. AAMAS Workshops (2023)
Vaishak Belle
Toward A Logical Theory Of Fairness and Bias. Theory Pract. Log. Program. 23 (4) (2023)
Vaishak Belle
Tractable Probabilistic Models for Ethical AI. ICCS (2022)
Ioannis Papantonis, Vaishak Belle
Principled Diverse Counterfactuals in Multilinear Models. CoRR (2022)
Gary Smith, Vaishak Belle, Ronald P. A. Petrick
Intention Recognition With ProbLog. Frontiers Artif. Intell. 5 (2022)
Ameer Saadat-Yazdi, Xue Li, Sandrine Chausson, Vaishak Belle, Björn Ross, Jeff Z. Pan, Nadin Kökciyan
KEViN: A Knowledge Enhanced Validity and Novelty Classifier for Arguments. ArgMining@COLING (2022)
Xin Du, Bénédicte Legastelois, Bhargavi Ganesh, Ajitha Rajan, Hana Chockler, Vaishak Belle, Stuart Anderson, Subramanian Ramamoorthy
Vision Checklist: Towards Testable Error Analysis of Image Models to Help System Designers Interrogate Model Capabilities. CoRR (2022)
Till Hofmann, Vaishak Belle
Using Abstraction for Interpretable Robot Programs in Stochastic Domains. CoRR (2022)
Vaishak Belle
Analyzing generalized planning under nondeterminism. Artif. Intell. 307 (2022)
Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg
Efficient multi-agent epistemic planning: Teaching planners about nested belief. Artif. Intell. 302 (2022)
Ionela Georgiana Mocanu, Zhenxu Yang, Vaishak Belle
Breaking CAPTCHA with Capsule Networks. Neural Networks 154 (2022)
Nick Hoernle, Rafael-Michael Karampatsis, Vaishak Belle, Kobi Gal
MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks. AAAI (2022)
Till Hofmann, Vaishak Belle
Abstracting Noisy Robot Programs. CoRR (2022)
Andreas Bueff, Ioannis Papantonis, Auste Simkute, Vaishak Belle
Explainability in Machine Learning: a Pedagogical Perspective. CoRR (2022)
Miguel Ángel Méndez Lucero, Rafael-Michael Karampatsis, Enrique Bojorquez Gallardo, Vaishak Belle
Signal Perceptron: On the Identifiability of Boolean Function Spaces and Beyond. Frontiers Artif. Intell. 5 (2022)
Sándor Bartha, James Cheney, Vaishak Belle
One Down, 699 to Go: or, synthesising compositional desugarings. CoRR (2021)
Vaishak Belle, Ioannis Papantonis
Principles and Practice of Explainable Machine Learning. Frontiers Big Data 4 (2021)
Michael Varley, Vaishak Belle
Fairness in machine learning with tractable models. Knowl. Based Syst. 215 (2021)
Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg
Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief. CoRR (2021)
Jonathan Feldstein, Vaishak Belle
Lifted reasoning meets weighted model integration. UAI (2021)
Sándor Bartha, James Cheney, Vaishak Belle
One down, 699 to go: or, synthesising compositional desugarings. Proc. ACM Program. Lang. 5 (OOPSLA) (2021)
Paulius Dilkas, Vaishak Belle
Weighted model counting with conditional weights for Bayesian networks. UAI (2021)
Nicholas Hoernle, Rafael-Michael Karampatsis, Vaishak Belle, Kobi Gal
MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks. CoRR (2021)
Alexander Philipp Rader, Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learning Implicitly with Noisy Data in Linear Arithmetic. IJCAI (2021)
Ioannis Papantonis, Vaishak Belle
Closed-Form Results for Prior Constraints in Sum-Product Networks. Frontiers Artif. Intell. 4 (2021)
Andreas Bueff, Stefanie Speichert, Vaishak Belle
Probabilistic Tractable Models in Mixed Discrete-Continuous Domains. Data Intell. 3 (2) (2021)
Lewis Hammond, Vaishak Belle
Learning tractable probabilistic models for moral responsibility and blame. Data Min. Knowl. Discov. 35 (2) (2021)
Paulius Dilkas, Vaishak Belle
Weighted Model Counting Without Parameter Variables. SAT (2021)
Gary Smith, Ron Petrick, Vaishak Belle
Intent Recognition in Smart Homes with ProbLog. PerCom Workshops (2021)
Ioannis Papantonis, Vaishak Belle
On Constraint Definability in Tractable Probabilistic Models. CoRR (2020)
Laszlo Treszkai, Vaishak Belle
A correctness result for synthesizing plans with loops in stochastic domains. Int. J. Approx. Reason. 119 (2020)
Paulius Dilkas, Vaishak Belle
Generating Random Logic Programs Using Constraint Programming. CP (2020)
Anton Fuxjaeger, Vaishak Belle
Logical Interpretations of Autoencoders. ECAI (2020)
Vaishak Belle
Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite Domains. SUM (2020)
Vaishak Belle
Logic, Probability and Action: A Situation Calculus Perspective. CoRR (2020)
Vaishak Belle, Ioannis Papantonis
Principles and Practice of Explainable Machine Learning. CoRR (2020)
Vaishak Belle, Hector J. Levesque
Regression and progression in stochastic domains. Artif. Intell. 281 (2020)
Anton Fuxjaeger, Vaishak Belle
Scaling up Probabilistic Inference in Linear and Non-linear Hybrid Domains by Leveraging Knowledge Compilation. ICAART (2) (2020)
Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Polynomial-Time Implicit Learnability in SMT. ECAI (2020)
Vaishak Belle
Logic, Probability and Action: A Situation Calculus Perspective. SUM (2020)
Amélie Levray, Vaishak Belle
Learning Credal Sum-Product Networks. AKBC (2020)
Vaishak Belle
Abstracting probabilistic models: Relations, constraints and beyond. Knowl. Based Syst. 199 (2020)
Paulius Dilkas, Vaishak Belle
Generating Random Logic Programs Using Constraint Programming. CoRR (2020)
Vaishak Belle, Luc De Raedt
Semiring programming: A semantic framework for generalized sum product problems. Int. J. Approx. Reason. 126 (2020)
Vaishak Belle
Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains. CoRR (2020)
Ioannis Papantonis, Vaishak Belle
Interventions and Counterfactuals in Tractable Probabilistic Models: Limitations of Contemporary Transformations. CoRR (2020)
Vaishak Belle
SMT + ILP. CoRR (2020)
Alexander Philipp Rader, Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learning Implicitly with Noisy Data in Linear Arithmetic. CoRR (2020)
Michael Varley, Vaishak Belle
Fairness in Machine Learning with Tractable Models. CoRR (2019)
Drew Hemment, Ruth Aylett, Vaishak Belle, Dave Murray-Rust, Ewa Luger, Jane Hillston, Michael Rovatsos, Frank Broz
Experiential AI. AI Matters 5 (1) (2019)
Vaishak Belle
The Quest for Interpretable and Responsible Artificial Intelligence. CoRR (2019)
Stefanie Speichert, Vaishak Belle
Learning Probabilistic Logic Programs over Continuous Data. ILP (2019)
Laszlo Treszkai, Vaishak Belle
A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains. CoRR (2019)
Vaishak Belle, Brendan Juba
Implicitly learning to reason in first-order logic. NeurIPS (2019)
Amélie Levray, Vaishak Belle
Learning Tractable Probabilistic Models in Open Worlds. CoRR (2019)
Drew Hemment, Ruth Aylett, Vaishak Belle, Dave Murray-Rust, Ewa Luger, Jane Hillston, Michael Rovatsos, Frank Broz
Experiential AI. CoRR (2019)
Anton Fuxjaeger, Vaishak Belle
Logical Interpretations of Autoencoders. CoRR (2019)
Vaishak Belle, Brendan Juba
Implicitly Learning to Reason in First-Order Logic. CoRR (2019)
Vaishak Belle
Probabilistic Planning by Probabilistic Programming. CoRR (2018)
Andreas Bueff, Stefanie Speichert, Vaishak Belle
Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks. CoRR (2018)
Vaishak Belle
Probabilistic Planning by Probabilistic Programming. AAAI Workshops (2018)
Vaishak Belle, Hector J. Levesque
Reasoning about discrete and continuous noisy sensors and effectors in dynamical systems. Artif. Intell. 262 (2018)
Stefanie Speichert, Vaishak Belle
Learning Probabilistic Logic Programs in Continuous Domains. CoRR (2018)
Lewis Hammond, Vaishak Belle
Deep Tractable Probabilistic Models for Moral Responsibility. CoRR (2018)
Vaishak Belle, Hector J. Levesque
Reasoning about Discrete and Continuous Noisy Sensors and Effectors in Dynamical Systems. CoRR (2018)
Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting
Efficient Symbolic Integration for Probabilistic Inference. IJCAI (2018)
Anton Fuxjaeger, Vaishak Belle
Scaling up Probabilistic Inference in Linear and Non-Linear Hybrid Domains by Leveraging Knowledge Compilation. CoRR (2018)
Vaishak Belle
On Plans With Loops and Noise. AAMAS (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vaishak Belle