Hypothesis-driven Stream Learning with Augmented Memory. - Mengmi Zhang; Rohil Badkundri; Morgan B. Talbot; Gabriel Kreiman (CoRR, 2021)

Learning to Learn: How to Continuously Teach Humans and Machines. - Parantak Singh; You Li; Ankur Sikarwar; Weixian Lei; Daniel Gao; Morgan Bruce Talbot; Ying Sun 001; Mike Zheng Shou; Gabriel Kreiman; Mengmi Zhang (CoRR, 2022)

Learning to Learn: How to Continuously Teach Humans and Machines. - Parantak Singh; You Li; Ankur Sikarwar; Weixian Lei; Difei Gao; Morgan B. Talbot; Ying Sun 001; Mike Zheng Shou; Gabriel Kreiman; Mengmi Zhang (ICCV, 2023)

L-WISE: Boosting Human Image Category Learning Through Model-Based Image Selection And Enhancement. - Morgan B. Talbot; Gabriel Kreiman; James J. DiCarlo; Guy Gaziv (CoRR, 2024)

L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement. - Morgan Bruce Talbot; Gabriel Kreiman; James J. DiCarlo; Guy Gaziv (ICLR, 2025)

Tuned Compositional Feature Replays for Efficient Stream Learning. - Morgan B. Talbot; Rushikesh Zawar; Rohil Badkundri; Mengmi Zhang; Gabriel Kreiman (IEEE Trans. Neural Networks Learn. Syst., 2025)

Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance. - Lorenzo Tausani; Paolo Muratore; Morgan B. Talbot; Giacomo Amerio; Gabriel Kreiman; Davide Zoccolan (CoRR, 2025)