Uri T. Eden
Orcid: 0000-0002-2058-3691
According to our database1,
Uri T. Eden
authored at least 45 papers
between 2004 and 2024.
Collaborative distances:
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Bibliography
2024
Integrating Big Data, Artificial Intelligence, and motion analysis for emerging precision medicine applications in Parkinson's Disease.
J. Big Data, December, 2024
A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data.
IEEE Access, 2024
2022
Direct Discriminative Decoder Models for Analysis of High-Dimensional Dynamical Neural Data.
Neural Comput., 2022
Integrating Statistical and Machine Learning Approaches to Identify Receptive Field Structure in Neural Populations.
CoRR, 2022
IEEE Access, 2022
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022
2021
Proceedings of the 10th International IEEE/EMBS Conference on Neural Engineering, 2021
2020
Assessing Goodness-of-Fit in Marked Point Process Models of Neural Population Coding via Time and Rate Rescaling.
Neural Comput., 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
Efficient Decoding of Multi-Dimensional Signals From Population Spiking Activity Using a Gaussian Mixture Particle Filter.
IEEE Trans. Biomed. Eng., 2019
Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach.
Neural Comput., 2019
State-Space Global Coherence to Estimate the Spatio-Temporal Dynamics of the Coordinated Brain Activity.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
Continuous Prediction of Cognitive State Using A Marked-Point Process Modeling Framework.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
Capturing Spike Variability in Noisy Izhikevich Neurons Using Point Process Generalized Linear Models.
Neural Comput., 2018
A common goodness-of-fit framework for neural population models using marked point process time-rescaling.
J. Comput. Neurosci., 2018
A Comparison Study of Point-Process Filter and Deep Learning Performance in Estimating Rat Position Using an Ensemble of Place Cells.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
Parameter Estimation in Synaptic Coupling Model Using a Point Process Modeling Framework<sup>*</sup>.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
2017
Predicting learning dynamics in Multiple-Choice Decision-Making Tasks using a variational Bayes technique.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
2015
An Approach to Time-Frequency Analysis With Ridges of the Continuous Chirplet Transform.
IEEE Trans. Signal Process., 2015
Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter.
Neural Comput., 2015
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015
Estimating a dynamic state to relate neural spiking activity to behavioral signals during cognitive tasks.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015
2014
NeuroImage, 2014
Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.
Frontiers Comput. Neurosci., 2014
Proceedings of the 22nd Mediterranean Conference on Control and Automation, 2014
2013
IEEE Trans. Biomed. Eng., 2013
Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone.
PLoS Comput. Biol., 2013
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013
2011
A General Likelihood Framework for Characterizing the Time Course of Neural Activity.
Neural Comput., 2011
Using point process models to describe rhythmic spiking in the subthalamic nucleus of Parkinson's patients.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
2010
Using Point Process Models to Compare Neural Spiking Activity in the Subthalamic Nucleus of Parkinson's Patients and a Healthy Primate.
IEEE Trans. Biomed. Eng., 2010
2009
Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1.
Neural Comput., 2009
Using point process models to determine the impact of visual cues on basal ganglia activity and behavior of Parkinson's patients.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009
2008
A mixed filter algorithm for cognitive state estimation from simultaneously recorded continuous and binary measures of performance.
Biol. Cybern., 2008
Proceedings of the IEEE International Conference on Acoustics, 2008
Modeling neural spiking activity in the sub-thalamic nucleus of Parkinson's patients and a healthy primate.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008
2007
Construction of Point Process Adaptive Filter Algorithms for Neural Systems Using Sequential Monte Carlo Methods.
IEEE Trans. Biomed. Eng., 2007
Proceedings of the 46th IEEE Conference on Decision and Control, 2007
Proceedings of the 46th IEEE Conference on Decision and Control, 2007
2006
NeuroImage, 2006
A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals.
Neural Comput., 2006
2004
Neural Comput., 2004