Texture recognition underpins critical applications in industrial quality control, robotic manipulation, and biomedical imaging. Traditional deep dictionary learning methods for texture recognition ...

Theorists propose that the brain constantly generates implicit predictions that guide information processing. During language comprehension, such predictions have indeed been observed, but it remains ...

Run python preprocess.py to construct HM-graph for TUDataset. Change the parameter of drop_node() function in the ops.py to drop noises in the motif dictionary. Run python preprocess_hiv.py and python ...

Implementation and example training scripts of various flavours of graph neural network in TensorFlow 2.0. Much of it is based on the code in the tf-gnn-samples repo. The code is maintained by the ...

Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States Institute for Molecular Engineering and Materials Science Division, Argonne National Laboratory, ...

Modern microscopes create a data deluge with gigabytes of data generated each second, and terabytes per day. Storing and processing this data is a severe bottleneck, not fully alleviated by data ...

† Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 675 Nelson Rising Lane NS 416A, San Francisco, California 94143, United States ‡ Department of ...

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that ...

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural ...