3 citations · 11 across the 8 of their papers we have counts for
8 papers
Contrastive Self-Supervised Learning As Neural Manifold Packing
Guanming Zhang, David J. Heeger, Stefano Martiniani
Contrastive self-supervised learning based on point-wise comparisons has been widely studied for vision tasks. In the visual cortex of the brain, neuronal responses to distinct sti…
Unconditional stability of a recurrent neural circuit implementing divisive normalization
Shivang Rawat, David J. Heeger, Stefano Martiniani
Stability in recurrent neural models poses a significant challenge, particularly in developing biologically plausible neurodynamical models that can be seamlessly trained. Traditio…
Adaptive coding efficiency in recurrent cortical circuits via gain control
Lyndon R. Duong, Colin Bredenberg, David J. Heeger +1
Sensory systems across all modalities and species exhibit adaptation to continuously changing input statistics. Individual neurons have been shown to modulate their response gains…
Adaptive whitening in neural populations with gain-modulating interneurons
Lyndon R. Duong, David Lipshutz, David J. Heeger +2
Statistical whitening transformations play a fundamental role in many computational systems, and may also play an important role in biological sensory systems. Existing neural circ…
Heading perception and the structure of the optic acceleration field
Charlie S. Burlingham, Mengjian Hua, Oliver Xu +2
Visual estimation of heading in the human brain is widely believed to be based on instantaneous optic flow, the velocity of retinal image motion. However, we previously found that…
Epistemic AI platform accelerates innovation by connecting biomedical knowledge
Da Chen Emily Koo, Heather Bowling, Kenneth Ashworth +2
Epistemic AI accelerates biomedical discovery by finding hidden connections in the network of biomedical knowledge. The Epistemic AI web-based software platform embodies the concep…
Time-Series Analysis via Low-Rank Matrix Factorization Applied to Infant-Sleep Data
Sheng Liu, Mark Cheng, Hayley Brooks +4
We propose a nonparametric model for time series with missing data based on low-rank matrix factorization. The model expresses each instance in a set of time series as a linear com…
ORGaNICs: A Theory of Working Memory in Brains and Machines
David J. Heeger, Wayne E. Mackey
Working memory is a cognitive process that is responsible for temporarily holding and manipulating information. Most of the empirical neuroscience research on working memory has fo…