# Papers

**Principles and Practice of Explainable Machine Learning.**

*Frontiers in Big Data*, 2021.

I. Papantonis and V. Belle.

**Lifted Reasoning Meets Weighted Model Integration**

*UAI*, 2021.

J. Feldstein and V. Belle.

**Weighted Model Counting with Conditional Weights for Bayesian Networks.**

*UAI*, 2021.

P. Dilkas and V. Belle.

**Weighted Model Counting Without Parameter Variables.**

*SAT*, 2021.

P. Dilkas and V. Belle.

**Learning Implicitly with Noisy Data in Linear Arithmetic.**

*IJCAI*, 2021.

A. Rader, I. Mocanu, V. Belle, and B. Juba.

**Closed-Form Results for Prior Constraints in Sum-Product Networks.**

*Frontiers in artificial intelligence*, 2021.

I. Papantonis and V. Belle.

**Fairness in Machine Learning with Tractable Models.**

*Knowledge-Based Systems*, 2021.

M. Varley and V. Belle.

**Tractable Probabilistic Models for Moral Responsibility and Blame.**

*Data Mining and Knowledge Discovery*, 2021.

L. Hammond and V. Belle.

**Probabilistic Tractable Models in Mixed Discrete-Continuous Domains.**

*Data Intelligence*, 2021.

A. Bueff, S. Speichert and V. Belle.

**Semiring Programming: A Semantic Framework for Generalized Sum Product Problems.**

*International Journal of Approximate Reasoning*, 2020.

V. Belle and L. De Raedt.

**A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains**.

*ICAPS (Journal Track)*, 2020.

L. Treszkai and V. Belle.

**Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains**.

*SUM*, 2020.

V. Belle.

**Implicitly Learning to Reason in First-Order Logic (Extended Abstract)**.

*KR*, 2020.

V. Belle and B. Juba.

**Abstracting Probabilistic Models: Relations, Constraints and Beyond (Extended Abstract)**.

*KR*, 2020.

V. Belle.

**Generating Random Logic Programs Using Constraint Programming**.

*CP*, 2020.

P. Dilkas and V. Belle.

**Logic, Probability and Action: A Situation Calculus Perspective**.

*SUM*, 2020.

V. Belle.

**Learning Credal Sum-Product Networks**.

*AKBC*, 2020.

A. Levray and V. Belle.

**Abstracting Probabilistic Models: Relations, Constraints and Beyond**.

*Knowledge-based Systems*, 2020.

V. Belle.

**Regression and Progression in Stochastic Domains**.

*Artificial Intelligence*, 2020.

V. Belle and H. Levesque.

**Logical Interpretations of Autoencoders**.

*ECAI*, 2020.

A. Fuxjaeger and V. Belle.

**Polynomial-time Implicit Learnability in SMT**.

*ECAI*, 2020.

I. Mocanu, V. Belle and B. Juba.

**A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains**.

*International Journal of Approximate Reasoning*, 2020.

L. Treszkai and V. Belle.

*ICAART*, 2020.

A. Fuxjaeger and V. Belle.

**Fairness in Machine Learning with Tractable Models**.

*AAAI Workshop: Statistical Relational Artificial Intelligence*, 2020.

M. Varley and V. Belle.

**Abstracting Probabilistic Models: A Logical Perspective**.

*AAAI Workshop: Statistical Relational Artificial Intelligence*, 2020.

V. Belle.

*AAAI Workshop: Statistical Relational Artificial Intelligence*, 2020.

V. Belle.

**Semiring Programming: A Declarative Framework for Generalized Sum Product Problems**.

*AAAI Workshop: Statistical Relational Artificial Intelligence*, 2020.

V. Belle and L. De Raedt.

*AAAI Workshop: Statistical Relational Artificial Intelligence*, 2020.

A. Fuxjaeger and V. Belle.

**Implicitly Learning to Reason in First-Order Logic**.

*NeurIPS*, 2019.

V. Belle and B. Juba.

**The quest for interpretable and responsible artificial intelligence**.

*The Biochemist*, 2019.

V. Belle.

**Logical Interpretations of Autoencoders**.

*NeurIPS Workshop on Knowledge Representation & Reasoning Meets Machine Learning*, 2019.

A. Fuxjaeger and V. Belle.

**Tractable Probabilistic Models for Moral Responsibility**.

*NeurIPS Workshop on Knowledge Representation & Reasoning Meets Machine Learning*, 2019.

L. Hammond and V. Belle.

*NeurIPS Workshop on Knowledge Representation & Reasoning Meets Machine Learning*, 2019.

I. Mocanu, V. Belle and B. Juba.

**Interventions and Counterfactuals in Tractable Probabilistic Models**.

*NeurIPS Workshop on Knowledge Representation & Reasoning Meets Machine Learning*, 2019.

I. Papantonis and V. Belle.

**Implicitly Learning to Reason in First-Order Logic**.

*Fourth International Workshop on Declarative Learning Based Programming (DeLBP 2019)*, 2019.

V. Belle and B. Juba.

**Learning Probabilistic Logic Programs in Continuous Domains**.

*ILP*, 2019.

S. Speichert and V. Belle.

*Best student paper award*

**Toward Fairness, Morality and Transparency in Artificial Intelligence through Experiential AI**.

*Leonardo*, 2019.

D. Hemment, V. Belle, R. Aylett, D. Murray-Rust, L. Pschetz and F. Broz.

**Deep Tractable Probabilistic Models for Moral Responsibility**.

*Human-Like Computing Third Wave of AI Workshop*, 2019.

L. Hammond and V. Belle.

*AI Matters*, 5(1):25-31, 2019.

D. Hemment, R. Aylett, V. Belle, D. Murray-Rust, E. Luger, J. Hillston, M. Rovatsos and F. Broz.

**Learning Symbolic Representations in Mixed Discrete-Continuous Domains**.

*Human-Like Computing Third Wave of AI Workshop*, 2019.

S. Speichert, A. Bueff and V. Belle.

**On Plans With Loops and Noise**.

*AAMAS*, 2018.

V. Belle.

**Probabilistic Planning by Probabilistic Programming**.

*AAAI Workshop on Planning and Inference*, 2018.

V. Belle.

**Reasoning about discrete and continuous noisy sensors and effectors in dynamical systems**.

*Artificial Intelligence*, 262:189 - 221, 2018.

V. Belle and H. Levesque.

**Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks**.

*Workshop on Hybrid Reasoning, Workshop Learning (HRL 2018), KR*, 2018.

A. Bueff, S. Speichert and V. Belle.

**Efficient Symbolic Integration for Probabilistic Inference**.

*IJCAI*, 2018.

S. Kolb, M. Mladenov, S. Sanner, V. Belle and K. Kersting.

**Planning in hybrid relational MDPs**.

*ICAPS (Journal Track)*, 2018.

D. Nitti, V. Belle, T. De Laet and L. De Raedt.

**Learning Probabilistic Logic Programs in Continuous Domains**.

*Workshop on Hybrid Reasoning, Workshop Learning (HRL 2018), KR*, 2018.

S. Speichert and V. Belle.

**Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds**.

*IJCAI*, 2017.

V. Belle.

**Weighted Model Counting With Function Symbols**.

*UAI*, 2017.

V. Belle.

**Open-Universe Weighted Model Counting**.

*AAAI*, 2017.

V. Belle.

**Open-Universe Weighted Model Counting: Extended Abstract**.

*AAAI Workshop: Symbolic Inference and Optimization*, 2017.

V. Belle.

**Reasoning about Probabilities in Unbounded First-Order Dynamical Domains**.

*IJCAI*, 2017.

V. Belle and G. Lakemeyer.

**Solving Probability Problems in Natural Language**.

*IJCAI*, 2017.

A. Dries, A. Kimmig, J. Davis, V. Belle and L. De Raedt.

**Solving Probability Problems in Natural Language**.

*ILP*, 2017.

A. Dries, A. Kimmig, J. Davis, V. Belle and L. De Raedt.

**The Symbolic Interior Point Method**.

*AAAI*, 2017.

M. Mladenov, V. Belle and K. Kersting.

**Planning in hybrid relational MDPs**.

*Machine Learning*:1-28, 2017.

D. Nitti, V. Belle, T. De Laet and L. De Raedt.

**A First-Order Logic of Probability and Only Knowing in Unbounded Domains**.

*AAAI*, 2016.

V. Belle, G. Lakemeyer and H. Levesque.

**Action-Centric Probabilistic Programming**.

*StarAI Workshop at IJCAI*, 2016.

V. Belle.

**Component Caching in Hybrid Domains with Piecewise Polynomial Densities**.

*AAAI*, 2016.

V. Belle, G. Van den Broeck and A. Passerini.

**Foundations for Generalized Planning in Unbounded Stochastic Domains**.

*KR*, 2016.

V. Belle and H. Levesque.

**Hashing-based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report**.

*IJCAI*, 2016.

V. Belle, G. Van den Broeck and A. Passerini.

**Satisfiability and Model Counting in Open Universes**.

*Beyond NP Workshop, AAAI*, 2016.

V. Belle.

**Multi-Agent Only Knowing on Planet Kripke**.

*IJCAI*, 2015.

G. Aucher and V. Belle.

**Only Knowing Meets Common Knowledge**.

*IJCAI*, 2015.

V. Belle and G. Lakemeyer.

**Probabilistic Inference in Hybrid Domains by Weighted Model Integration**.

*IJCAI*, 2015.

V. Belle, A. Passerini and G. Van den Broeck.

**ALLEGRO: Belief-based Programming in Stochastic Dynamical Domains**.

*IJCAI*, 2015.

V. Belle and H. J. Levesque.

**Probabilistic Inference in Hybrid Domains by Weighted Model Integration**.

*Workshop on Hybrid Reasoning, IJCAI*, 2015.

V. Belle, A. Passerini and G. Van den Broeck.

**A Logical Theory of Localization**.

*Studia Logica*:1-32, 2015.

V. Belle and H. Levesque.

**Hashing-based Approximate Probabilistic Inference in Hybrid Domains**.

*UAI*, 2015.

V. Belle, G. Van den Broeck and A. Passerini.

*Best paper award*

**Robot location estimation in the situation calculus**.

*Journal of Applied Logic*, 13:397-413, 2015.

V. Belle and H. Levesque.

**Semantical Considerations on Multiagent Only Knowing**.

*Artificial Intelligence*, 223:1-26, 2015.

V. Belle and G. Lakemeyer.

**Planning Over Multi-Agent Epistemic States: A Classical Planning Approach**.

*AAAI*, 2015.

C. Muise, V. Belle, P. Felli, S. A. McIlraith, T. Miller, A. R. Pearce and L. Sonenberg.

**Planning Over Multi-Agent Epistemic States: A Classical Planning Approach (Amended Version)**.

*Workshop on Distributed and Multi-Agent Planning, ICAPS*, 2015.

C. Muise, V. Belle, P. Felli, S. A. McIlraith, T. Miller, A. R. Pearce and L. Sonenberg.

**Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming**.

*European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases*, 2015.

D. Nitti, V. Belle and L. De Raedt.

*Machine learning journal best student paper award.*

**Sample-based abstraction for hybrid relational MDPs**.

*European Workshop on Reinforcement Learning, ICML*, 2015.

Davide Nitti, V. Belle, T. De Laet and Luc De Raedt.

**A Logical Theory of Robot Localization**.

*AAMAS*, 2014.

V. Belle and H. J. Levesque.

**A Logical Theory of Robot Localization**.

*AAAI Spring Symposium: Knowledge Representation and Reasoning in Robotics*, 2014.

V. Belle and H. J. Levesque.

**PREGO: An Action Language for Belief-Based Cognitive Robotics in Continuous Domains**.

*Cognitive Robotics Workshop*, 2014.

V. Belle and H. J. Levesque.

**How to Progress Beliefs in Continuous Domains**.

*KR*, 2014.

V. Belle and H. J. Levesque.

**Multiagent Only Knowing in Dynamic Systems**.

*Journal of Artificial Intelligence Research*, 49:363-402, 2014.

V. Belle and G. Lakemeyer.

**On the Progression of Knowledge in Multiagent Systems**.

*KR*, 2014.

V. Belle and G. Lakemeyer.

**On the Projection Problem in Active Knowledge Bases with Incomplete Information**.

*AI Matters*, 1(2):14-16, 2014.

V. Belle.

**PREGO: An Action Language for Belief-Based Cognitive Robotics in Continuous Domains**.

*AAAI*, 2014.

V. Belle and H. J. Levesque.

**Review of programming with higher-order logic by Dale Miller and Gopalan Nadathur**.

*SIGACT News*, 45(2):32-35, 2014.

V. Belle.

**Nondeterministic Planning with Conditional Effects**.

*ICAPS*, 2014.

C. Muise, S. McIlraith and V. Belle.

**Computing Contingent Plans via Fully Observable Non-Deterministic Planning**.

*ICAPS Workshop: Models and Paradigms for Planning under Uncertainty*, 2014.

C. J. Muise, S. A. McIlraith and V. Belle.

**Computing Contingent Plans via Fully Observable Non-Deterministic Planning**.

*AAAI*, 2014.

C. J. Muise, S. A. McIlraith and V. Belle.

**A Formal Model of Belief under Continuous Uncertainty**.

*Non-Classical Logics*, 2013.

V. Belle and H. J. Levesque.

**Probabilistic State Estimation in the Situation Calculus**.

*IJCAI Workshop: Weighted Logics for Artificial Intelligence*, 2013.

V. Belle and H. J. Levesque.

**Reasoning about Continuous Uncertainty in the Situation Calculus**.

*IJCAI*, 2013.

V. Belle and H. J. Levesque.

**Reasoning about Motion Kinematics with Continuous Uncertainty in the Situation Calculus**.

*IJCAI Workshop: Nonmonotonic Reasoning, Action and Change*, 2013.

V. Belle and H. J. Levesque.

**Reasoning about Probabilities in Dynamic Systems using Goal Regression**.

*UAI*, 2013.

V. Belle and H. J. Levesque.

**Robot Location Estimation in the Situation Calculus**.

*ICAPS Workshop: Planning and Robotics*, 2013.

V. Belle and H. J. Levesque.

**Robot Location Estimation in the Situation Calculus**.

*Symposium on Logical Formalizations of Commonsense Reasoning*, 2013.

V. Belle and H. J. Levesque.

**On the Projection Problem in Active Knowledge Bases with Incomplete Information**.

PhD thesis, Dept. of Computer Science, RWTH Aachen University, 2012.

V. Belle.

**A Semantical Account of Progression in the Presence of Uncertainty**.

*AAAI*, 2011.

V. Belle and G. Lakemeyer.

**Multi-Agent Only-Knowing**.

*Knowing, Reasoning, and Acting: Essays in Honour of H. J. Levesque*. College Publications, 2011.

V. Belle and G. Lakemeyer.

**On Progression and Query Evaluation in First-Order Knowledge Bases with Function Symbols**.

*IJCAI*, 2011.

V. Belle and G. Lakemeyer.

**Review of from zero to infinity: what makes numbers interesting by Constance Reid**.

*SIGACT News*, 42(2), 2011.

V. Belle.

**Multi-Agent Only-Knowing Revisited**.

*KR*, 2010.

V. Belle and G. Lakemeyer.

**Multi-Agent Only-Knowing Revisited**.

*AlgoSyn*, 2010.

V. Belle.

**Reasoning about Imperfect Information Games in the Epistemic Situation Calculus**.

*AAAI*, 2010.

V. Belle and G. Lakemeyer.

**Detection and Recognition of Human Faces using Random Forests for a Mobile Robot**.

Masterâ€™s thesis, Dept. of Computer Science, RWTH Aachen University, 2008.

V. Belle.

**Randomized trees for real-time one-step face detection and recognition**.

*ICPR*, 2008.

V. Belle, T. Deselaers and S. Schiffer.