A tradeoff between generalization and perceptual capacity in recurrent neural networks. - Taylor W. Webb; Steven Frankland; Simon N. Segert; Alexander A. Petrov; Randall C. O'Reilly; Jonathan Cohen 003 (CogSci, 2019)

Maximum Entropy Function Learning. - Simon N. Segert; Jonathan Cohen 003 (CogSci, 2022)

A Self-Supervised Framework for Function Learning and Extrapolation. - Simon N. Segert; Jonathan D. Cohen 003 (Trans. Mach. Learn. Res., 2022)

Beyond Transformers for Function Learning. - Simon N. Segert; Jonathan Cohen 003 (CogSci, 2023)

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem. - Simon N. Segert (ICLR, 2024)

A Group Theoretic Analysis of the Symmetries Underlying Base Addition and Their Learnability by Neural Networks. - Cutter Dawes; Simon N. Segert; Kamesh Krishnamurthy; Jonathan D. Cohen 003 (CoRR, 2025)