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 An Algebraic Approach to Moralisation and Triangulation of Probabilistic Graphical ModelsConference on Algebra and Coalgebra in Computer Science (CALCO), 2025 |
 Reinforcement Learning in Categorical CyberneticsElectronic Proceedings in Theoretical Computer Science (EPTCS), 2024 |
 Going Beyond Neural Network Feature Similarity: The Network Feature
Complexity and Its Interpretation Using Category TheoryInternational Conference on Learning Representations (ICLR), 2023 |
 Enriching Disentanglement: From Logical Definitions to Quantitative
MetricsNeural Information Processing Systems (NeurIPS), 2023 |
 A Category-theoretical Meta-analysis of Definitions of DisentanglementInternational Conference on Machine Learning (ICML), 2023 |
 The Compositional Structure of Bayesian InferenceInternational Symposium on Mathematical Foundations of Computer Science (MFCS), 2023 |
 Quantifying Consistency and Information Loss for Causal Abstraction
LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2023 |
 Computing with Categories in Machine LearningArtificial General Intelligence (AGI), 2023 |
 Markov Categories and EntropyIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022 |
 The d-separation criterion in Categorical ProbabilityJournal of machine learning research (JMLR), 2022 |
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 Free gs-monoidal categories and free Markov categoriesApplied Categorical Structures (ACS), 2022 |
 Weakly supervised causal representation learningNeural Information Processing Systems (NeurIPS), 2022 |
 Categorical composable cryptographyFoundations of Software Science and Computation Structure (FOSSACS), 2021 |
 Compositional Abstraction Error and a Category of Causal ModelsConference on Uncertainty in Artificial Intelligence (UAI), 2021 |
 Compositional Semantics for Probabilistic Programs with Exact
ConditioningLogic in Computer Science (LICS), 2021 |
 Functorial Manifold LearningElectronic Proceedings in Theoretical Computer Science (EPTCS), 2020 |
