Authors: Adway Mitra, Palash Dey
arXiv
In district-based multi-party elections, electors cast votes in their respective districts. In each district, the party with maximum votes wins the corresponding seat in the governing body. Election S...
Authors: Karthik Sriram, Dhruv Gupta, Rajiv Parikh
arXiv
We develop a Bayesian modeling framework to address a pressing real-life problem faced by the police in tackling insurgent gangs. Unlike criminals associated with common crimes such as robbery, theft...
Authors: Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss
arXiv
Cognitive maps are a proposed concept on how the brain efficiently organizes memories and retrieves context out of them. The entorhinal-hippocampal complex is heavily involved in episodic and relation...
Authors: Geoff Boeing, Clemens Pilgram, Yougeng Lu
arXiv
This study estimates the relationships between street network characteristics and transport-sector CO2 emissions across every urban area in the world and investigates whether they are the same across...
Authors: Manuele Leonelli, Gherardo Varando
arXiv
Staged trees are a relatively recent class of probabilistic graphical models that extend Bayesian networks to formally and graphically account for non-symmetric patterns of dependence. Machine learnin...
Authors: Paul B. May, Andrew O. Finley, Ralph O. Dubayah
arXiv
The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar instrument that collects near-global measurements of forest structure. While expansive in scope, GEDI samples are spatially spa...
Authors: Solmaz Seifollahi, Hossein Bevrani, Zakariya Yahya Algamal
arXiv
In this paper, we propose the application of shrinkage strategies to estimate coefficients in the Bell regression models when prior information about the coefficients is available. The Bell regression...
Authors: Johan Medrano, Abderrahmane Kheddar, Sofiane Ramdani
arXiv
Correlation coefficients play a pivotal role in quantifying linear relationships between random variables. Yet, their application to time series data is very challenging due to temporal dependencies....
Authors: Veronica Tora, Justin Torok, Michiel Bertsch, Ashish Raj
arXiv
One of the hallmarks of Alzheimer's disease (AD) is the accumulation and spread of toxic aggregates of tau protein. The progression of AD tau pathology is thought to be highly stereotyped, which is in...
Authors: Thiyanga S. Talagala
arXiv
The rapid evolution in the fields of computer science, data science, and artificial intelligence has significantly transformed the utilisation of data for decision-making. Data visualisation plays a c...
Authors: Jikai Jin, Vasilis Syrgkanis
arXiv
We study causal representation learning, the task of recovering high-level latent variables and their causal relationships in the form of a causal graph from low-level observed data (such as text and...
Authors: Wala Draidi Areed, Aiden Price, Helen Thompson, Conor Hassan, Reid Malseed, Kerrie Mengersen
arXiv
Spatial statistical models are commonly used in geographical scenarios to ensure spatial variation is captured effectively. However, spatial models and cluster algorithms can be complicated and expens...
Authors: Chantal Bécourt, Sandrine Luce, Ute C Rogner, Christian Boitard
arXiv
We previously demonstrated that the abrogation of the ICOS pathway prevents type 1 diabetes development in the Non Obese Diabetic (NOD) mouse, but results in a CD4+ T-cell dependent autoimmune neuromy...
Authors: André Beauducel, Norbert Hilger
arXiv
The present study investigates to what degree the common variance of the factor score predictor with the original factor, i.e., the determinacy coefficient or the validity of the factor score predicto...
Authors: Jacob A. Johnson, Matthew J. Heaton, William F. Christensen, Lynsie R. Warr, Summer B. Rupper
arXiv
Autoencoders are powerful machine learning models used to compress information from multiple data sources. However, autoencoders, like all artificial neural networks, are often unidentifiable and unin...