Strictly Frequentist Imprecise Probability
Fröhlich, Christian, Rabanus Derr, and Robert C Williamson. 2024. “Strictly Frequentist Imprecise Probability”. International Journal of Approximate Reasoning 168 (109148).
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Limits to Predicting Online Speech Using Large Language Models
Remeli, Mina, Moritz Hardt, and Robert C. Williamson. 2024. “Limits to Predicting Online Speech Using Large Language Models”. ArXiv.
Environmental Intelligence: Context and Rhetoric
Williamson, Robert C. 2025. “Environmental Intelligence: Context and Rhetoric”. Harvard Data Science Review 7 (4).
Systems of Precision: Coherent Probabilities on Pre-Dynkin Systems and Coherent Previsions on Linear Subspaces
Derr, Rabanus, and Robert C. Williamson. 2023. “Systems of Precision: Coherent Probabilities on Pre-Dynkin Systems and Coherent Previsions on Linear Subspaces”. Entropy 25 (9): 1283.
Causal modelling without introducing counterfactuals or abstract distributions
Höltgen, Benedikt, and Robert C. Williamson. 2024. “Causal Modelling Without Introducing Counterfactuals or Abstract Distributions”. ArXiv.
An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm
Pacheco, Armando J. Cabrera, Rabanus Derr, and Robert C. Williamson. 2024. “An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm”. ArXiv.
Geometry and Stability of Supervised Learning Problems
Mémoli, Facundo, Brantley Vose, and Robert C. Williamson. 2025. “Geometry and Stability of Supervised Learning Problems”. Journal of Machine Learning Research 26 (221): 1-99.
The Geometry and Calculus of Losses
Williamson, Robert C, and Zac Cranko. 2023. “The Geometry and Calculus of Losses”. Journal of Machine Learning Research 24 (342): 1-72.
On the Richness of Calibration
Höltgen, Benedikt, and Robert C Williamson. 2023. “On the Richness of Calibration”. In FAccT2023 .
The Geometry of Mixability
Cabrera.Pacheco, Armando J., and Robert C Williamson. 2023. “The Geometry of Mixability”. Transactions on Machine Learning Research.