Systematic errors in the formant analysis of steady-state vowels. - Gautam K. Vallabha; Betty Tuller (Speech Commun., 2002)

Network Analysis of Toxic Chemicals and Symptoms: Implications for Designing First-Responder Systems. - Suresh K. Bhavnani; Annie Abraham; Christopher Demeniuk; Meseret Gebrekristos; Abe Gong; Satyendra Nainwal; Gautam K. Vallabha; Rudy J. Richardson (AMIA, 2007)

Modeling Unsupervised Perceptual Category Learning. - Brenden M. Lake; Gautam K. Vallabha; James L. McClelland (IEEE Trans. Auton. Ment. Dev., 2009)

Nonlinear Dynamics in Speech Perception. - Betty Tuller; Noël Nguyen; Leonardo Lancia; Gautam K. Vallabha (Nonlinear Dynamics in Human Behavior, 2011)

Meta Arcade: A Configurable Environment Suite for Meta-Learning. - Edward W. Staley; Chace Ashcraft; Benjamin Stoler; Jared Markowitz; Gautam K. Vallabha; Christopher Ratto; Kapil D. Katyal (CoRR, 2021)

Lifelong Learning Metrics. - Alexander New; Megan M. Baker; Eric Q. Nguyen; Gautam K. Vallabha (CoRR, 2022)

L2Explorer: A Lifelong Reinforcement Learning Assessment Environment. - Erik C. Johnson; Eric Q. Nguyen; Blake Schreurs; Chigozie S. Ewulum; Chace Ashcraft; Neil M. Fendley; Megan M. Baker; Alexander New; Gautam K. Vallabha (CoRR, 2022)

Latent Properties of Lifelong Learning Systems. - Corban G. Rivera; Chace Ashcraft; Alexander New; James Schmidt; Gautam K. Vallabha (CoRR, 2022)

Enabling local learning for generative-replay-based continual learning with a recurrent model of the insect memory center. - Raphael Norman-Tenazas; Isaac Western; Gautam K. Vallabha; Matthew J. Roos; Erik C. Johnson; Brian S. Robinson (ICONS, 2023)

Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence. - Erik C. Johnson; Brian S. Robinson; Gautam K. Vallabha; Justin Joyce; Jordan K. Matelsky; Raphael Norman-Tenazas; Isaac Western; Marisel Villafañe-Delgado; Martha Cervantes; Michael S. Robinette; Arun V. Reddy; Lindsey Kitchell; et al. (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)