Qualitative comparisons of the proposed algorithm with 7 state-of-the-art algorithms in 4 representative CT-MRI image pairs. by Ayush Dogra (17054597)

Qualitative comparisons of the proposed algorithm with 7 state-of-the-art algorithms in 4 representative CT-MRI image pairs. by Ayush Dogra (17054597)

Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition by Shiying Wang (5179559)

“…In this work, we study the complex impact of multi-state functional connectivity on behaviors by analyzing the data from a recent landmark brain development and child health study. …”

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. …”

Signal detection algorithm adapted from [1] yields exponential distributions and unrealistic mean durations of percepts. by Quynh-Anh Nguyen (847240)

“…(Bottom) Trial-by-trial applications of the signal detection algorithm from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>] with A: <i>C</i>_<i>th</i> = 4.01 and B: <i>C</i>_<i>th</i> = 4.21 yield exponentially distributed subsequent percept durations for <i>I</i> (blue) and <i>S</i> (red). …”

CEC2017 basic functions. by Tengfei Ma (597633)

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Application of multi-scale community detection to subject-level and group-level resting state functional brain networks. by Arian Ashourvan (6685232)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

“…<p>^<b>a</b>PATH⁺ shows comparable or better performance with less overfitting, as evidenced by a smaller slope, with much less increase in RMSEs beyond the training dataset, compared to established binding affinity prediction algorithms spanning a variety of methods. The benchmarked algorithms include physics-based and deep learning algorithms from the famous AutoDock framework (scoring function of AutoDock4 implemented in the AutoDockFR package [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref068" target="_blank">68</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref077" target="_blank">77</a>], Vinardo [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref069" target="_blank">69</a>], GNINA [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref070" target="_blank">70</a>]), empirical (AA-Score [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref071" target="_blank">71</a>]), knowledge-based (SMoG2016 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref072" target="_blank">72</a>]), and deep learning-based scoring functions (OnionNet [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref073" target="_blank">73</a>], PLANET [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref074" target="_blank">74</a>]). …”

CEC2017 test function test results. by Tengfei Ma (597633)

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(a-c) Sampling event times with an intensity function . by Gerrit Großmann (9585147)

Iteration curves of different algorithms. by Tengfei Ma (597633)

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Flowchart of OP-ZOA algorithm. by Tengfei Ma (597633)

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IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

The signal detection algorithm for constructing a neurometric function (the probability of segregation as a function of time) generates acceptable buildup fits at <i>DF</i> = 1, 3,... by Quynh-Anh Nguyen (847240)

“…Lower panel: The signal detection algorithm constructs neurometric functions using numerical data from all <i>N</i>_<i>in</i> neuronal units. …”

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b>⁰ (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

Process of the transformation from the EV-TOP to the EV1-COP and the EV2-SP. by Fengjie Fu (7314347)

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