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Nicholas Turk-Browne

2 accepted papers

2022

How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?

NeurIPS 2022accept

Humans learn from visual inputs at multiple timescales, both rapidly and flexibly acquiring visual knowledge over short periods, and robustly accumulating online learning progress over longer periods. Modeling these powerful learning capabilities is an important problem for computational visual cogn…

Cited by 25SourcePDFScholar
2020

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence

NeurIPS 2020spotlight

Functional magnetic resonance imaging (fMRI) is a crucial technology for gaining insights into cognitive processes in humans. Data amassed from fMRI measurements result in volumetric data sets that vary over time. However, analysing such data presents a challenge due to the large degree of noise and…