Eli Shlizerman
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Explore the profile of Eli Shlizerman including associated specialties, affiliations and a list of published articles.
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Articles
21
Citations
168
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Recent Articles
1.
Hazelden J, Liu Y, Shlizerman E, Shea-Brown E
ArXiv
. 2023 Dec;
PMID: 38045480
Training networks consisting of biophysically accurate neuron models could allow for new insights into how brain circuits can organize and solve tasks. We begin by analyzing the extent to which...
2.
Li J, Le T, Shlizerman E
IEEE Trans Neural Netw Learn Syst
. 2023 Aug;
35(11):16966-16974.
PMID: 37581978
Action recognition from temporal multivariate sequences of features, such as identifying human actions, is typically approached by supervised training as it requires many ground truth annotations to reach high recognition...
3.
Biswas R, Shlizerman E
PLoS Comput Biol
. 2022 Nov;
18(11):e1010653.
PMID: 36374908
The representation of the flow of information between neurons in the brain based on their activity is termed the causal functional connectome. Such representation incorporates the dynamic nature of neuronal...
4.
Xiang J, Colburn S, Majumdar A, Shlizerman E
Appl Opt
. 2022 Mar;
61(9):2173-2183.
PMID: 35333231
In recent years, convolutional neural networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast forward propagation runtime to process high-resolution visual streams in real time. This...
5.
Biswas R, Shlizerman E
Front Syst Neurosci
. 2022 Mar;
16:817962.
PMID: 35308566
Representation of brain network interactions is fundamental to the translation of neural structure to brain function. As such, methodologies for mapping neural interactions into structural models, i.e., inference of functional...
6.
Su K, Shlizerman E
Front Artif Intell
. 2021 Mar;
3:70.
PMID: 33733187
Encoder-decoder recurrent neural network models (RNN Seq2Seq) have achieved success in ubiquitous areas of computation and applications. They were shown to be effective in modeling data with both temporal and...
7.
8.
Kim J, Leahy W, Shlizerman E
Front Comput Neurosci
. 2019 Apr;
13:8.
PMID: 30930759
Connectivity and biophysical processes determine the functionality of neuronal networks. We, therefore, developed a real-time framework, called Neural Interactome, to simultaneously visualize and interact with the structure and dynamics of...
9.
Functional connectomics from neural dynamics: probabilistic graphical models for neuronal network of
Liu H, Kim J, Shlizerman E
Philos Trans R Soc Lond B Biol Sci
. 2018 Sep;
373(1758).
PMID: 30201841
We propose an approach to represent neuronal network dynamics as a probabilistic graphical model (PGM). To construct the PGM, we collect time series of neuronal responses produced by the neuronal...
10.
Barreiro A, Kutz J, Shlizerman E
J Math Neurosci
. 2017 Oct;
7(1):10.
PMID: 29019105
We examine a family of random firing-rate neural networks in which we enforce the neurobiological constraint of Dale's Law-each neuron makes either excitatory or inhibitory connections onto its post-synaptic targets....