Learning Without a Global Clock: Asynchronous Learning in a Physics-Driven Learning Network. - Jacob F. Wycoff; Sam Dillavou; Menachem Stern; Andrea J. Liu; Douglas J. Durian (CoRR, 2022)

Bellybutton: Accessible and Customizable Deep-Learning Image Segmentation. - Sam Dillavou; Jesse M. Hanlan; Anthony T. Chieco; Hongyi Xiao; Sage Fulco; Kevin T. Turner; Douglas J. Durian (CoRR, 2023)

Machine Learning Without a Processor: Emergent Learning in a Nonlinear Electronic Metamaterial. - Sam Dillavou; Benjamin D. Beyer; Menachem Stern; Marc Z. Miskin; Andrea J. Liu; Douglas J. Durian (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Comparing information content of representation spaces for disentanglement with VAE ensembles. - Kieran A. Murphy; Sam Dillavou; Dani S. Bassett (CoRR, 2024)

Comparing the information content of probabilistic representation spaces. - Kieran A. Murphy; Sam Dillavou; Danielle S. Bassett (Trans. Mach. Learn. Res., 2025)