Skip to main content
Main Menu
Utility Menu
Search
HARVARD.EDU
Pehlevan Group
neural foundations of natural and artificial intelligence
Home
People
News
Publications
Resources
Teaching
About
Positions
HOME
/
Publications
BibTex
Tagged
XML
2019
C. Pehlevan and D. B. Chklovskii
, “
Neuroscience-inspired online unsupervised learning algorithms
,”
IEEE Signal Processing Magazine
, vol. 36, no. 6, pp. 88-96, 2019.
PDF
C. Pehlevan
, “
A Spiking Neural Network with Local Learning Rules Derived From Nonnegative Similarity Matching
,” in
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
, 2019.
PDF
2018
V. Minden, C. Pehlevan, and D. B. Chklovskii
, “
Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
,” in
2018 52nd Asilomar Conference on Signals, Systems, and Computers
, 2018.
A. Giovannucci, V. Minden, C. Pehlevan, and D. B. Chklovskii
, “
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching
,” in
IEEE International Conference on Big Data
, 2018.
G. Guralnik, Z. Guralnik, and C. Pehlevan
, “
Holography, Fractals and the Weyl Anomaly
,”
arXiv preprint arXiv:1802.05362
, 2018.
C. Pehlevan, F. Ali, and B. P. Ölveczky
, “
Flexibility in motor timing constrains the topology and dynamics of pattern generator circuits
,”
Nature communications
, vol. 9, no. 1, pp. 977, 2018.
A. Sengupta, M. Tepper, C. Pehlevan, A. Genkin, and D. Chklovskii
, “
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
,” in
Advances in neural information processing systems (NeurIPS)
, 2018.
C. Pehlevan, A. M. Sengupta, and D. B. Chklovskii
, “
Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?
”
Neural computation
, vol. 30, no. 1, pp. 84–124, 2018.
2017
C. Pehlevan, S. Mohan, and D. B. Chklovskii
, “
Blind nonnegative source separation using biological neural networks
,”
Neural computation
, vol. 29, no. 11, pp. 2925–2954, 2017.
C. Pehlevan, A. Genkin, and D. B. Chklovskii
, “
A clustering neural network model of insect olfaction
,” in
2017 51st Asilomar Conference on Signals, Systems, and Computers
, 2017, pp. 593–600.
C. Pehlevan and A. Sengupta
, “
Resource-efficient perceptron has sparse synaptic weight distribution
,” in
Signal Processing and Communications Applications Conference (SIU), 2017 25th
, 2017, pp. 1–4.
2016
R. Abbasi-Asl, C. Pehlevan, B. Yu, and D. Chklovskii
, “
Do retinal ganglion cells project natural scenes to their principal subspace and whiten them?
” in
Signals, Systems and Computers, 2016 50th Asilomar Conference on
, 2016, pp. 1641–1645.
C. Pehlevan, P. Paoletti, and L. Mahadevan
, “
Integrative neuromechanics of crawling in D. melanogaster larvae
,”
Elife
, vol. 5, pp. e11031, 2016.
Y. Chen, C. Pehlevan, and D. B. Chklovskii
, “
Self-calibrating neural networks for dimensionality reduction
,” in
Signals, Systems and Computers, 2016 50th Asilomar Conference on
, 2016, pp. 1488–1495.
2015
T. M. Otchy, et al.
, “
Acute off-target effects of neural circuit manipulations
,”
Nature
, vol. 528, no. 7582, pp. 358, 2015.
C. Pehlevan, T. Hu, and D. B. Chklovskii
, “
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data
,”
Neural computation
, vol. 27, no. 7, pp. 1461–1495, 2015.
C. Pehlevan and D. Chklovskii
, “
A normative theory of adaptive dimensionality reduction in neural networks
,” in
Advances in neural information processing systems (NeurIPS)
, 2015, pp. 2269–2277.
C. Pehlevan and D. B. Chklovskii
, “
Optimization theory of hebbian/anti-hebbian networks for pca and whitening
,” in
Communication, Control, and Computing (Allerton), 2015 53rd Annual Allerton Conference on
, 2015, pp. 1458–1465.
2014
Z. Guralnik, C. Pehlevan, and G. Guralnik
, “
On exact statistics and classification of ergodic systems of integer dimension
,”
Chaos
, vol. 24, no. 2, pp. 023125, 2014.
C. Pehlevan and D. B. Chklovskii
, “
A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features
,” in
Signals, Systems and Computers, 2014 48th Asilomar Conference on
, 2014, pp. 769–775.
Pages
first
«
1
2
3
4
5
»
last