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Tamara von Glehn

2 accepted papers

2024

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

ICML 2024poster

We present our position on the elusive quest for a general-purpose framework for specifying and studying deep learning architectures. Our opinion is that the key attempts made so far lack a coherent bridge between specifying constraints which models must satisfy and specifying their implementations.…

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2021

Grounded Language Learning Fast and Slow

ICLR 2021spotlight

Recent work has shown that large text-based neural language models acquire a surprising propensity for one-shot learning. Here, we show that an agent situated in a simulated 3D world, and endowed with a novel dual-coding external memory, can exhibit similar one-shot word learning when trained with c…