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researcher

Daniel M. Bear

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedBrain-Like Object Recognition with High-Performing Shallow Recurrent ANNs

108 citations · 151 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2020★ 43 cited

Learning Physical Graph Representations from Visual Scenes

Daniel M. Bear, Chaofei Fan, Damian Mrowca +8

Convolutional Neural Networks (CNNs) have proved exceptional at learning representations for visual object categorization. However, CNNs do not explicitly encode objects, parts, an…

cs.LG2020

Visual Grounding of Learned Physical Models

Yunzhu Li, Toru Lin, Kexin Yi +5

Humans intuitively recognize objects' physical properties and predict their motion, even when the objects are engaged in complicated interactions. The abilities to perform physical…

cs.CV2019★ 108 cited

Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs

Jonas Kubilius, Martin Schrimpf, Kohitij Kar +11

Deep convolutional artificial neural networks (ANNs) are the leading class of candidate models of the mechanisms of visual processing in the primate ventral stream. While initially…

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