research
∙
05/18/2023
Learning low-dimensional dynamics from whole-brain data improves task capture
The neural dynamics underlying brain activity are critical to understand...
share
research
∙
04/15/2023
SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training
Federated learning (FL) enables the training of a model leveraging decen...
research
∙
11/29/2022
Self-Supervised Mental Disorder Classifiers via Time Reversal
Data scarcity is a notable problem, especially in the medical domain, du...
research
∙
06/13/2022
Geometrically Guided Integrated Gradients
Interpretability methods for deep neural networks mainly focus on the se...
research
∙
05/18/2022
Constraint-Based Causal Structure Learning from Undersampled Graphs
Graphical structures estimated by causal learning algorithms from time s...
research
∙
02/04/2022
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series
Recently, methods that represent data as a graph, such as graph neural n...
research
∙
12/31/2021
Single-Shot Pruning for Offline Reinforcement Learning
Deep Reinforcement Learning (RL) is a powerful framework for solving com...
research
∙
12/07/2021
A deep learning model for data-driven discovery of functional connectivity
Functional connectivity (FC) studies have demonstrated the overarching v...
research
∙
11/01/2021
Multi network InfoMax: A pre-training method involving graph convolutional networks
Discovering distinct features and their relations from data can help us ...
research
∙
11/01/2021
Brain dynamics via Cumulative Auto-Regressive Self-Attention
Multivariate dynamical processes can often be intuitively described by a...
research
∙
05/03/2021
Fusing multimodal neuroimaging data with a variational autoencoder
Neuroimaging studies often involve the collection of multiple data modal...
research
∙
01/06/2020
Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia
Objective: Multimodal measurements of the same phenomena provide complem...
research
∙
12/09/2019
Grouped sparse projection
As evident from deep learning, very large models bring improvements in t...
research
∙
11/16/2019
Transfer Learning of fMRI Dynamics
As a mental disorder progresses, it may affect brain structure, but brai...
research
∙
04/24/2019
Prediction of Progression to Alzheimer`s disease with Deep InfoMax
Arguably, unsupervised learning plays a crucial role in the majority of ...
research
∙
04/04/2018
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR
The wide variety of brain imaging technologies allows us to exploit info...
research
∙
04/02/2018
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
In the NIPS 2017 Learning to Run challenge, participants were tasked wit...
research
∙
11/01/2017
Almost instant brain atlas segmentation for large-scale studies
Large scale studies of group differences in healthy controls and patient...
research
∙
12/03/2016
End-to-end learning of brain tissue segmentation from imperfect labeling
Segmenting a structural magnetic resonance imaging (MRI) scan is an impo...
research
∙
02/25/2016