most citedRepresentational dissimilarity metric spaces for stochastic neural networks

10 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2023

Adaptive whitening with fast gain modulation and slow synaptic plasticity

Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii +1

Neurons in early sensory areas rapidly adapt to changing sensory statistics, both by normalizing the variance of their individual responses and by reducing correlations between the…

q-bio.NC2023★ 3 cited

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…

q-bio.NC2023★ 1 cited

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…

cs.LG2022★ 10 cited

Representational dissimilarity metric spaces for stochastic neural networks

Lyndon R. Duong, Jingyang Zhou, Josue Nassar +3

Quantifying similarity between neural representations -- e.g. hidden layer activation vectors -- is a perennial problem in deep learning and neuroscience research. Existing methods…

eess.IV2022

Multi-rate adaptive transform coding for video compression

Lyndon R. Duong, Bohan Li, Cheng Chen +1

Contemporary lossy image and video coding standards rely on transform coding, the process through which pixels are mapped to an alternative representation to facilitate efficient d…