The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)

Function <i>χ</i>_<i>opt</i> superimposed with the phase-field function indicating the channel geometry. by Martina Bukač (20161460)

The control algorithm of MPC for SSI. by Ahmed Abdelaleem (19066115)

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …”

TV-BayesOpt algorithm performance for tracking a gradual drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. by John E. Fleming (8533956)

“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”

TV-BayesOpt algorithm performance for tracking a periodic drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. by John E. Fleming (8533956)

“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”

TV-BayesOpt algorithm performance for tracking a superimposed (gradual and periodic) drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. by John E. Fleming (8533956)

“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”

Taming Negative Ion Resonances Using Nonlocal Exchange-Correlation Functionals by Abhisek Ghosal (762577)

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Comparison the results with and without Fourier Loss Function for Rain100H. by Chaobing Zheng (20896579)

Comparison results of phase trajectories and local enlarged images between two systems. by Haoran Cui (7235234)

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Comparison between the proposed framework with and without Fourier Loss Function for Rain100H. by Chaobing Zheng (20896579)

Diagram of the algorithm used during the training phase. by Ana P. Arantes (17131753)

Flowchart of the phase optimization algorithm. by Maxim Terekhov (3429614)

“…<p>At stage II, phase vectors {Φ^top} providing cost function values F_c above 90% of maximum are selected as initial condition {Φ₀} for iterative NLS-search and selection of the optimum vectors {Φ^opt}. …”

Available functions in the phase-shifting package. by Raul Castañeda (13932971)

Available functions in the phase reconstruction package. by Raul Castañeda (13932971)

Connectivity characteristics (distance, orientation, and region) of the stable low-|Δθ|, stable high-|Δθ|, and shifting-|Δθ| networks. by Melisa Menceloglu (7610213)

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Scatter plots showing the relationships between PCV (phase clustering value) and 3D inter-site distance for representative frequencies (rows) for the five behavioral conditions (co... by Melisa Menceloglu (7610213)

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Fig 2 - by Melisa Menceloglu (7610213)

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Representative connections in the stable low-|Δθ| (left columns), stable high-|Δθ| (middle columns), and shifting-|Δθ| (right, highlighted columns) networks, for representative fre... by Melisa Menceloglu (7610213)

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Inter-site temporal power correlations (top row), average powers (middle row), and inter-site-pair correlations between inter-site power correlation and average power (bottom row)... by Melisa Menceloglu (7610213)

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