Authors: Divya K. Bilolikar, Aishwarya More, Aella Gong, Joseph Janssen
arXiv
Predictions are a central part of water resources research. Historically, physically-based models have been preferred; however, they have largely failed at modeling hydrological processes at a catchme...
Authors: Martin Saveski, Steven Jecmen, Nihar B. Shah, Johan Ugander
arXiv
Peer review assignment algorithms aim to match research papers to suitable expert reviewers, working to maximize the quality of the resulting reviews. A key challenge in designing effective assignment...
Authors: Gonzalo Maximiliano Lopez, Juan Pablo Aparicio
arXiv
In the modeling of parasite transmission dynamics, understanding the reproductive characteristics of these parasites is crucial. This paper presents a mathematical model that explores the reproduct...
Authors: Felix A. Wichmann, Robert Geirhos
arXiv
Deep neural networks (DNNs) are machine learning algorithms that have revolutionised computer vision due to their remarkable successes in tasks like object classification and segmentation. The success...
Authors: Mario Figueira-Pereira, Xavier Barber, David Conesa, Antonio LĂłpez-QuĂlez, JoaquĂn MartĂnez-Minaya, Iosu Paradinas, Maria Grazia Pennino
arXiv
In ecology we may find scenarios where the same phenomenon (species occurrence, species abundance, etc.) is observed using two different types of samplers. For instance, species data can be collected...
Authors: Guilherme Pombo, Robert Gray, Amy P. K. Nelson, Chris Foulon, John Ashburner, Parashkev Nachev
arXiv
Causal mapping of the functional organisation of the human brain requires evidence of \textit{necessity} available at adequate scale only from pathological lesions of natural origin. This demands infe...
Authors: Tong Zhou
arXiv
This paper presents a hidden Markov model designed to investigate the complex nature of earnings persistence. The proposed model assumes that the residuals of log-earnings consist of a persistent comp...
Authors: Dozie Iwuh
arXiv
What Quantum Brain Dynamics (QBD) considers is not just these other functions of the brain, this is because they can be well analyzed with the workings of classical mechanics (even though they still p...
Authors: Arisina Banerjee, Arun K Kuchibhotla
arXiv
Central limit theorems (CLTs) have a long history in probability and statistics. They play a fundamental role in constructing valid statistical inference procedures. Over the last century, various tec...
Authors: Aaron J. Molstad, Yanwei Cai, Alexander P. Reiner, Charles Kooperberg, Wei Sun, Li Hsu
arXiv
Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies req...
Authors: Denizhan Pak, Donsuk Lee, Samantha M. W. Wood, Justin N. Wood
arXiv
Recent progress in artificial intelligence has renewed interest in building machines that learn like animals. Almost all of the work comparing learning across biological and artificial systems comes f...
Authors: Jianhao Ding, Zhaofei Yu, Tiejun Huang, Jian K. Liu
arXiv
The success of deep learning in the past decade is partially shrouded in the shadow of adversarial attacks. In contrast, the brain is far more robust at complex cognitive tasks. Utilizing the advantag...
Authors: John Rushby
arXiv
A singular attribute of humankind is our ability to undertake novel, cooperative behavior, or teamwork. This requires that we can communicate goals, plans, and ideas between the brains of individuals...
Authors: Xavier Brouty, Matthieu Garcin
arXiv
Considering that both the entropy-based market information and the Hurst exponent are useful tools for determining whether the efficient market hypothesis holds for a given asset, we study the link be...
Authors: Zijing Yang, Chengfeng Zhang, Yawen Hou, Zheng Chen
arXiv
In clinical follow-up studies with a time-to-event end point, the difference in the restricted mean survival time (RMST) is a suitable substitute for the hazard ratio (HR). However, the RMST only meas...