Authors: Jingjing Fan, Kevin Sitek, Bharath Chandrasekaran, Abhra Sarkar
arXiv
Understanding the dynamics of functional brain connectivity patterns using noninvasive neuroimaging techniques is an important focus in human neuroscience. Vector autoregressive (VAR) processes and Gr...
Authors: Armin W. Thomas, Christopher RĂ©, Russell A. Poldrack
arXiv
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., perceiving fear or joy) and brain activity...
Authors: Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
arXiv
Several deep neural networks have recently been shown to generate activations similar to those of the brain in response to the same input. These algorithms, however, remain largely implausible: they r...
Authors: Xinyi Liu, Gabriel Wallin, Yunxiao Chen, Irini Moustaki
arXiv
Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that th...
Authors: B. G. Palm, D. I. Alves, V. T. Vu, M. I. Pettersson, F. M. Bayer, R. J. Cintra, R. Machado, P. Dammert, H. Hellsten
arXiv
Change detection is an important synthetic aperture radar (SAR) application, usually used to detect changes on the ground scene measurements in different moments in time. Traditionally, change detecti...
Authors: Jakub Fil, Neil Dalchau, Dominique Chu
arXiv
Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli, to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and as such, does not...
Authors: Yukang Jiang, Ting Tian, Huajun Xie, Hailiang Guo, Xueqin Wang
arXiv
Amidst the COVID-19 pandemic, travel restrictions have emerged as crucial interventions for mitigating the spread of the virus. In this study, we enhance the predictive capabilities of our model, Sequ...
Authors: Jackson Cates, Randy C. Hoover, Kyle Caudle, Cagri Ozdemir, Karen Braman, David Machette
arXiv
In the era of big data, there is an increasing demand for new methods for analyzing and forecasting 2-dimensional data. The current research aims to accomplish these goals through the combination of t...
Authors: Simon Dahan, Logan Z. J. Williams, Abdulah Fawaz, Daniel Rueckert, Emma C. Robinson
arXiv
The extension of convolutional neural networks (CNNs) to non-Euclidean geometries has led to multiple frameworks for studying manifolds. Many of those methods have shown design limitations resulting i...
Authors: Ludwig A. Hothorn
arXiv
Standard ANOVA is among the most widely used tests in the life sciences and beyond. Several alternatives are proposed to provide simultaneous confidence intervals, ensure tight control of FWER, be rob...
Authors: Caston Sigauke, Rosinah Mukhodobwane, Wilbert Chagwiza, Winston Garira
arXiv
With the use of empirical data, this paper focuses on solving financial and investment issues involving extremal dependence of ten pairwise combinations of the five BRICS (Brazil, Russia, India, China...
Authors: Jorge RamĂrez-Ruiz, Dmytro Grytskyy, Chiara Mastrogiuseppe, Yamen Habib, RubĂ©n Moreno-Bote
arXiv
Most theories of behavior posit that agents tend to maximize some form of reward or utility. However, animals very often move with curiosity and seem to be motivated in a reward-free manner. Here we a...
Authors: U. Simola, A. Bonfanti, X. Dumusque, J. Cisewski-Kehe, S. Kaski, J. Corander
arXiv
Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for addressing stellar...
Authors: Rina Kagawa, Masanori Shiro
arXiv
The increasing demand for personalized health care has led to the expectation that individualized quantitative evaluation of human disease states is possible. However, this has not yet been achieved a...
Authors: Rob Trangucci, Yang Chen, Jon Zelner
arXiv
Characterizing the cumulative burden of COVID-19 by race/ethnicity is of the utmost importance for public health researchers and policy makers in order to design effective mitigation measures. This an...