Special issue on Combining Probability and Logic. - Jon Williamson; Dov M. Gabbay (J. Appl. Log., 2003)

Bayesianism and Language Change. - Jon Williamson (J. Log. Lang. Inf., 2003)

A Dynamic Interaction Between Machine Learning and the Philosophy of Science. - Jon Williamson (Minds Mach., 2004)

Objective Bayesian Nets. - Jon Williamson (We Will Show Them! (2), 2005)

Combining Argumentation and Bayesian Nets for Breast Cancer Prognosis. - Matthew Williams 001; Jon Williamson (J. Log. Lang. Inf., 2006)

Introduction. - Jon Williamson (J. Log. Lang. Inf., 2006)

Dispositional versus epistemic causality. - Jon Williamson (Minds Mach., 2006)

Objective Bayesian probabilistic logic. - Jon Williamson (J. Algorithms, 2008)

Objective Bayesianism with predicate languages. - Jon Williamson (Synth., 2008)

Possible Semantics for a Common Framework of Probabilistic Logics. - Rolf Haenni; Jan-Willem Romeijn; Gregory R. Wheeler; Jon Williamson (Interval / Probabilistic Uncertainty and Non-Classical Logics, 2008)

Objective Bayesian Nets for Systems Modelling and Prognosis in Breast Cancer. - Sylvia B. Nagl; Matthew Williams 001; Jon Williamson (Innovations in Bayesian Networks, 2008)

Combining Probability and Logic. - Fábio Gagliardi Cozman; Rolf Haenni; Jan-Willem Romeijn; Federica Russo; Gregory R. Wheeler; Jon Williamson (J. Appl. Log., 2009)

Aggregating Judgements by Merging Evidence. - Jon Williamson (J. Log. Comput., 2009)

The Philosophy of Science and its relation to Machine Learning. - Jon Williamson (Scientific Data Mining and Knowledge Discovery, 2010)

Recursive Bayesian Nets for Prediction, Explanation and Control in Cancer Science - A Position Paper. - Lorenzo Casini; Phyllis McKay Illari; Federica Russo; Jon Williamson (BIOINFORMATICS, 2010)

Objective Bayesianism, Bayesian conditionalisation and voluntarism. - Jon Williamson (Synth., 2011)

Objective Bayesianism and the Maximum Entropy Principle. - Jürgen Landes; Jon Williamson (Entropy, 2013)

From Bayesian epistemology to inductive logic. - Jon Williamson (J. Appl. Log., 2013)

Modelling mechanisms with causal cycles. - Brendan Clarke; Bert Leuridan; Jon Williamson (Synth., 2014)

Justifying Objective Bayesianism on Predicate Languages. - Jürgen Landes; Jon Williamson (Entropy, 2015)

Maximum Entropy Applied to Inductive Logic and Reasoning. - Jürgen Landes; Jon Williamson (Entropy, 2015)

Special issue: Combining probability and logic. - Jürgen Landes; Jon Williamson (J. Appl. Log., 2016)

Intervention and Identifiability in Latent Variable Modelling. - Jan-Willem Romeijn; Jon Williamson (Minds Mach., 2018)

Towards the entropy-limit conjecture. - Jürgen Landes; Soroush Rafiee Rad; Jon Williamson (Ann. Pure Appl. Log., 2021)

Establishing the teratogenicity of Zika and evaluating causal criteria. - Jon Williamson (Synth., 2021)

Correction to: Establishing the teratogenicity of Zika and evaluating causal criteria. - Jon Williamson (Synth., 2021)

Objective Bayesian Nets for Integrating Consistent Datasets. - Jürgen Landes; Jon Williamson (J. Artif. Intell. Res., 2022)

Determining Maximal Entropy Functions for Objective Bayesian Inductive Logic. - Jürgen Landes; Soroush Rafiee Rad; Jon Williamson (J. Philos. Log., 2023)

Explainable AI: definition and attributes of a good explanation for health AI. - Evangelia Kyrimi; Scott McLachlan; Jared M. Wohlgemut; Zane B. Perkins; David A. Lagnado; William Marsh 001; Alexander Gimson; Ali Shafti; Ari Ercole; Amitava Banerjee; Ben Glocker; Burkhard Schafer 001; et al. (AI Ethics, 2025)