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20242026
most citedModeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss for Enhanced Fidelity

4 citations · 7 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.NE2025

Identification of fixations and saccades in eye-tracking data using adaptive threshold-based method

Charles Orioma, Josef Krivan, Rujeena Mathema +4

Properties of ocular fixations and saccades are highly stochastic during many experimental tasks, and their statistics are often used as proxies for various aspects of cognition. A…

cs.NE2025

Jump-diffusion models of parametric volume-price distributions

Anup Budhathoki, Leonardo Rydin Gorjão, Pedro G. Lind +1

We present a data-driven framework to model the stochastic evolution of volume-price distribution from the New York Stock Exchange (NYSE) equities. The empirical distributions are…

cs.NE2025★ 2 cited

IntLevPy: A Python library to classify and model intermittent and Lévy processes

Shailendra Bhandari, Pedro Lencastre, Sergiy Denysov +2

IntLevPy provides a comprehensive description of the IntLevPy Package, a Python library designed for simulating and analyzing intermittent and Lévy processes. The package includes…

cs.NE2024★ 4 cited

Modeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss for Enhanced Fidelity

Shailendra Bhandari, Pedro Lencastre, Rujeena Mathema +3

Accurate modeling of eye gaze dynamics is essential for advancement in human-computer interaction, neurological diagnostics, and cognitive research. Traditional generative models l…

cs.NE2024★ 1 cited

Modeling stochastic eye tracking data: A comparison of quantum generative adversarial networks and Markov models

Shailendra Bhandari, Pedro Lincastre, Pedro Lind

We explore the use of quantum generative adversarial networks QGANs for modeling eye movement velocity data. We assess whether the advanced computational capabilities of QGANs can…