activity
20222025
most citedLearnable latent embeddings for joint behavioral and neural analysis

367 citations · 371 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Distinct Computations Emerge From Compositional Curricula in In-Context Learning

Jin Hwa Lee, Andrew K. Lampinen, Aaditya K. Singh +1

In-context learning (ICL) research often considers learning a function in-context through a uniform sample of input-output pairs. Here, we investigate how presenting a compositiona…

q-bio.NC2024★ 2 cited

Range, not Independence, Drives Modularity in Biologically Inspired Representations

Will Dorrell, Kyle Hsu, Luke Hollingsworth +6

Why do biological and artificial neurons sometimes modularise, each encoding a single meaningful variable, and sometimes entangle their representation of many variables? In this wo…

cs.CL2024

Geometric Signatures of Compositionality Across a Language Model's Lifetime

Jin Hwa Lee, Thomas Jiralerspong, Lei Yu +2

By virtue of linguistic compositionality, few syntactic rules and a finite lexicon can generate an unbounded number of sentences. That is, language, though seemingly high-dimension…

q-bio.NC2024★ 2 cited

Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning

Jin Hwa Lee, Stefano Sarao Mannelli, Andrew Saxe

Diverse studies in systems neuroscience begin with extended periods of curriculum training known as `shaping' procedures. These involve progressively studying component parts of mo…

cs.LG2022★ 367 cited

Learnable latent embeddings for joint behavioral and neural analysis

Steffen Schneider, Jin Hwa Lee, Mackenzie Weygandt Mathis

Mapping behavioral actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioral data increases, there is growing interest…