<p>We compared edge prediction performance between active and random learners, summarized over five trials. The dotted lines are drawn at one standard deviation from the mean in each direction. Active learner achieves higher accuracy and faster convergence than random learner.</p
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
All edges were found in each of 1000 network reconstructions from randomly subsampled data.</p
<p>The experiment consisted of 500 sample interventions, with an initial 500 sample observation. Whi...
<p>The results are summarized over five trials. The dotted lines are drawn at one standard deviation...
<p>Rows show inferred connections over a simulated cluster as a function of samples. Red and blue ed...
<p>Rows show misclassified edges in the adjacency matrices <i>W</i> and <i>H</i> as a function of sa...
Top and bottom rows respectively correspond to the precision-recall curves in scenario (S1) and scen...
<p>The plot is for the prediction task of the S350 dataset. The linear fit for GBT prediction [<a hr...
<p>A. Learning rate as a function of prediction error, SD of the generative distribution and treatme...
The peak of learned responding normally occurs at the learning stimulus itself, but can shift to a d...
The distributions of predictions scores are visualized using kernel density estimate over pose predi...
<p>(a) Regression based analysis of neuronal learning. Each row in the colormap shows an individual ...
For each of the 16 populations presented in Fig 4, one network was chosen at random at the end of th...
On average, participants gradually learned to choose outcomes correctly across six runs of scanned l...
<p>Reproducibility () vs prediction accuracy curves for two subjects: C Subject S4 (without motor ne...
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
All edges were found in each of 1000 network reconstructions from randomly subsampled data.</p
<p>The experiment consisted of 500 sample interventions, with an initial 500 sample observation. Whi...
<p>The results are summarized over five trials. The dotted lines are drawn at one standard deviation...
<p>Rows show inferred connections over a simulated cluster as a function of samples. Red and blue ed...
<p>Rows show misclassified edges in the adjacency matrices <i>W</i> and <i>H</i> as a function of sa...
Top and bottom rows respectively correspond to the precision-recall curves in scenario (S1) and scen...
<p>The plot is for the prediction task of the S350 dataset. The linear fit for GBT prediction [<a hr...
<p>A. Learning rate as a function of prediction error, SD of the generative distribution and treatme...
The peak of learned responding normally occurs at the learning stimulus itself, but can shift to a d...
The distributions of predictions scores are visualized using kernel density estimate over pose predi...
<p>(a) Regression based analysis of neuronal learning. Each row in the colormap shows an individual ...
For each of the 16 populations presented in Fig 4, one network was chosen at random at the end of th...
On average, participants gradually learned to choose outcomes correctly across six runs of scanned l...
<p>Reproducibility () vs prediction accuracy curves for two subjects: C Subject S4 (without motor ne...
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
All edges were found in each of 1000 network reconstructions from randomly subsampled data.</p
<p>The experiment consisted of 500 sample interventions, with an initial 500 sample observation. Whi...
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