Authors: Emmanuel Calvet, Bertrand Reulet, Jean Rouat
arXiv
Reservoir Computing (RC) is a paradigm in artificial intelligence where a recurrent neural network (RNN) is used to process temporal data, leveraging the inherent dynamical properties of the reservoir...
Authors: Li Fan, Jeova Farias Sales Rocha Neto
arXiv
The analysis of Synthetic Aperture Radar (SAR) imagery is an important step in remote sensing applications, and it is a challenging problem due to its inherent speckle noise. One typical solution is t...
Authors: Xuwen Hu, Jiaqi Qiu, Yu Lin, Inez Maria Zwetsloot, William Ka Fai Lee, Edmond Yin San Yeung, Colman Yiu Wah Yeung, Chris Chun Long Wong
arXiv
Prognostic Health Management (PHM) is designed to assess and monitor the health status of systems, anticipate the onset of potential failure, and prevent unplanned downtime. In recent decades, collect...
Authors: Colin Bredenberg, Cristina Savin
arXiv
Normative models of synaptic plasticity use a combination of mathematics and computational simulations to arrive at predictions of behavioral and network-level adaptive phenomena. In recent years, the...
Authors: David J Meer, Eric R. Weeks
arXiv
Distributions of strictly positive numbers are common and can be characterized by standard statistical measures such as mean, standard deviation, and skewness. We demonstrate that for these distributi...
Authors: Xiaoyu Chen, Changde Du, Qiongyi Zhou, Huiguang He
arXiv
The human brain can easily focus on one speaker and suppress others in scenarios such as a cocktail party. Recently, researchers found that auditory attention can be decoded from the electroencephalog...
Authors: Matthew J. Vowels
arXiv
Causal inference is a crucial goal of science, enabling researchers to arrive at meaningful conclusions regarding the predictions of hypothetical interventions using observational data. Path models, S...
Authors: Matthew Bonas, Christopher K. Wikle, Stefano Castruccio
arXiv
Among the most relevant processes in the Earth system for human habitability are quasi-periodic, ocean-driven multi-year events whose dynamics are currently incompletely characterized by physical mode...
Authors: Rohan Kumar Gupta, Rohit Sinha
arXiv
The primary method for identifying mental disorders automatically has traditionally involved using binary classifiers. These classifiers are trained using behavioral data obtained from an interview se...
Authors: Ying Jin, Kevin Guo, Dominik Rothenhäusler
arXiv
Many researchers have identified distribution shift as a likely contributor to the reproducibility crisis in behavioral and biomedical sciences. The idea is that if treatment effects vary across indiv...
Authors: Michela Gnaldi, Simone Del Sarto
arXiv
The Agenda 2030 recognises corruption as a major obstacle to sustainable development and integrates its reduction among SDG targets, in view of developing peaceful, just and strong institutions. In th...
Authors: Matthias Eckardt, Mehdi Moradi
arXiv
Within the applications of spatial point processes, it is increasingly becoming common that events are labeled by marks, prompting an exploration beyond the spatial distribution of events by incorpora...
Authors: Andrew R. Sedler, Chethan Pandarinath
arXiv
Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional neural activity for dow...
Authors: Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël C. -W. Phan
arXiv
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO network...
Authors: Nick Alonso, Jeff Krichmar
arXiv
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically...