Vladimir Itskov
Associate Professor of Mathematics
-
109B McAllister
University Park, PA - vui1@psu.edu
- 814-865-1613
Huck Affiliations
Publication Tags
Brain Neurons Neuron Code Sensing Layer Ring Hyperplane Noise Closed Encoding Decomposition Information Theory Quasiconvex Functions Rem Sleep Hippocampus Animals Pyramidal Cells Synapses Running Sleep Receptive Field Unknown Mathematics ExtractsMost Recent Publications
A Topological Approach to Inferring the Intrinsic Dimension of Convex Sensing Data.
Min-Chun Wu, Vladimir Itskov, Journal of Applied and Computational Topology on p. 49
A topological approach to inferring the intrinsic dimension of convex sensing data
Min Chun Wu, Vladimir Itskov, 2022, Journal of Applied and Computational Topology on p. 127-176
Hyperplane neural codes and the polar complex.
Vladimir Itskov, Alexander Kunin, Zvi Rosen, 2020, on p. 343-370
Hyperplane Neural Codes and the Polar Complex
Vladimir Itskov, Alexander Kunin, Zvi Rosen, 2020, on p. 343-369
On Open and Closed Convex Codes
Joshua Cruz, Chad Giusti, Vladimir Itskov, Bill Kronholm, 2019, Discrete and Computational Geometry on p. 247-270
Discrete biomathematics
Stephen F. Altschul, Mihai Pop, Joseph Rusinko, Elena Dimitrova, Andy Jenkins, Matthew Macauley, Qijun He, Svetlana Poznanovic, Carina Curto, Vladimir Itskov, Margaret Cozzens, 2017, on p. 1425-1514
Clique topology reveals intrinsic geometric structure in neural correlations
Chad Giusti, Eva Pastalkova, Carina Curto, Vladimir Itskov, 2015, Proceedings of the National Academy of Sciences of the United States of America on p. 13455-13460
A no-go theorem for one-layer feedforward networks
Chad Giusti, Vladimir Itskov, 2014, Neural Computation on p. 2527-2540
Encoding binary neural codes in networks of threshold-linear neurons
Carina Curto, Anda Degeratu, Vladimir Itskov, 2013, Neural Computation on p. 2858-2903
The Neural Ring: An Algebraic Tool for Analyzing the Intrinsic Structure of Neural Codes
Carina Curto, Vladimir Itskov, Alan Veliz-Cuba, Nora Youngs, 2013, The Bulletin of Mathematical Biophysics on p. 1571-1611
Most-Cited Papers
Clique topology reveals intrinsic geometric structure in neural correlations
Chad Giusti, Eva Pastalkova, Carina Curto, Vladimir Itskov, 2015, Proceedings of the National Academy of Sciences of the United States of America on p. 13455-13460
The Neural Ring: An Algebraic Tool for Analyzing the Intrinsic Structure of Neural Codes
Carina Curto, Vladimir Itskov, Alan Veliz-Cuba, Nora Youngs, 2013, The Bulletin of Mathematical Biophysics on p. 1571-1611
Combinatorial neural codes from a mathematical coding theory perspective
Carina Curto, Vladimir Itskov, Katherine Morrison, Zachary Roth, Judy L. Walker, 2013, Neural Computation on p. 1891-1925
A no-go theorem for one-layer feedforward networks
Chad Giusti, Vladimir Itskov, 2014, Neural Computation on p. 2527-2540
On Open and Closed Convex Codes
Joshua Cruz, Chad Giusti, Vladimir Itskov, Bill Kronholm, 2019, Discrete and Computational Geometry on p. 247-270
Encoding binary neural codes in networks of threshold-linear neurons
Carina Curto, Anda Degeratu, Vladimir Itskov, 2013, Neural Computation on p. 2858-2903
Hyperplane Neural Codes and the Polar Complex
Vladimir Itskov, Alexander Kunin, Zvi Rosen, 2020, on p. 343-369
A topological approach to inferring the intrinsic dimension of convex sensing data
Min Chun Wu, Vladimir Itskov, 2022, Journal of Applied and Computational Topology on p. 127-176
Discrete biomathematics
Stephen F. Altschul, Mihai Pop, Joseph Rusinko, Elena Dimitrova, Andy Jenkins, Matthew Macauley, Qijun He, Svetlana Poznanovic, Carina Curto, Vladimir Itskov, Margaret Cozzens, 2017, on p. 1425-1514
Hyperplane neural codes and the polar complex.
Vladimir Itskov, Alexander Kunin, Zvi Rosen, 2020, on p. 343-370