Ali Geisa — accepted AI-conference papers

2023

Polarity Is All You Need to Learn and Transfer Faster

Qingyang Wang, Michael Alan Powell, Eric W Bridgeford, Ali Geisa, Joshua T Vogelstein

ICML 2023poster

Natural intelligences (NIs) thrive in a dynamic world - they learn quickly, sometimes with only a few samples. In contrast, artificial intelligences (AIs) typically learn with a prohibitive number of training samples and computational power. What design principle difference between NI and AI could c…

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2023

Why do networks have inhibitory/negative connections?

Qingyang Wang, Mike A. Powell, Ali Geisa, Eric Bridgeford, Carey E. Priebe, Joshua T. Vogelstein

ICCV 2023poster

Why do brains have inhibitory connections? Why do deep networks have negative weights? We propose an answer from the perspective of representation capacity. We believe representing functions is the primary role of both (i) the brain in natural intelligence, and (ii) deep networks in artificial intel…

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