Search Results for author:
Found 9 papers, 2 papers with code
Hierarchical Bayesian inference for community detection and connectivity of functional brain networks
The method can robustly detect the group-level community structure of weighted functional networks that give rise to hidden brain states with an unknown number of communities and retain the variability of individual networks.
Unsupervised Representation Learning for 3D MRI Super Resolution with Degradation Adaptation
Yet, the difference in degradation representations between synthetic and authentic LR images suppresses the quality of SRR from authentic LR images.
Active Inference for Stochastic Control
Active inference has emerged as an alternative approach to control problems given its intuitive (probabilistic) formalism.
A mathematical perspective on edge-centric brain functional connectivity
Edge time series are increasingly used in brain functional imaging to study the node functional connectivity (nFC) dynamics at the finest temporal resolution while avoiding sliding windows.
Identification of brain states, transitions, and communities using functional MRI
Brain function relies on a precisely coordinated and dynamic balance between the functional integration and segregation of distinct neural systems.
An Active Learning Method for Diabetic Retinopathy Classification with Uncertainty Quantification
In recent years, deep learning (DL) techniques have provided state-of-the-art performance on different medical imaging tasks.
A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction
One of the roadblocks for accurate seizure prediction is scarcity of epileptic seizure data.
Dynamic causal modelling of COVID-19
This technical report describes a dynamic causal model of the spread of coronavirus through a population.
Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review
Here we provide a comprehensive review of state-of-the-art ML techniques in early prediction of seizures using EEG signals.
