Results 101 to 110 of about 11,282 (244)

Applying the maximum entropy principle to neural networks enhances multi‐species distribution models

Methods in Ecology and Evolution, EarlyView.
Abstract The increasing volume of presence‐only (PO) data generated by citizen science initiatives has greatly expanded biodiversity databases, but the statistical use of these data in species distribution models (SDMs) remains limited by strong sampling biases and the absence of reliable absence information.
Maxime Ryckewaert, Diego Marcos, Christophe Botella, Maximilien Servajean, Pierre Bonnet, Alexis Joly   +5 more
wiley   +1 more source

Assessing novelty, feasibility and value of creative ideas with an unsupervised approach using GPT‐4

British Journal of Psychology, EarlyView.
Abstract Creativity is defined by three key factors: novelty, feasibility and value. While many creativity tests focus primarily on novelty, they often neglect feasibility and value, thereby limiting their reflection of real‐world creativity. In this study, we employ GPT‐4, a large language model, to assess these three dimensions in a Japanese‐language
Felix B. Kern, Chien‐Te Wu, Zenas C. Chao   +2 more
wiley   +1 more source

Correction : Random-forest model for drug-target interaction prediction via Kullback-Leibler divergence. [PDF]

J Cheminform, 2022
Ahn S, Lee SE, Kim MH.
europepmc   +1 more source

Damage Identification by the Kullback-Leibler Divergence and Hybrid Damage Index [PDF]

, 2014
Shaohua Tian, Zhibo Yang, Zhengjia He, Xuefeng Chen   +3 more
openalex   +1 more source

Probabilistic learning inference of boundary value problem with uncertainties based on Kullback–Leibler divergence under implicit constraints [PDF]

, 2022
Christian Soize
openalex   +1 more source

The differences in essential facial areas for impressions between humans and deep learning models: An eye‐tracking and explainable AI approach

British Journal of Psychology, EarlyView.
Abstract This study explored the facial impressions of attractiveness, dominance and sexual dimorphism using experimental and computational methods. In Study 1, we generated face images with manipulated morphological features using geometric morphometrics. In Study 2, we conducted eye tracking and impression evaluation experiments using these images to
Takanori Sano, Jun Shi, Hideaki Kawabata
wiley   +1 more source

Generalizing machine learning models from clinical free text

Scientific Reports
To assess strategies for enhancing the generalizability of healthcare artificial intelligence models, we analyzed the impact of preprocessing approaches applied to medical free text, compared single- versus multiple-institution data models, and evaluated
Balaji Pandian, John Vandervest, Graciela Mentz, Jomy Varghese, Shavano D. Steadman, Sachin Kheterpal, Maggie Makar, V. G. Vinod Vydiswaran, Michael L. Burns   +8 more
doaj   +1 more source

Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model. [PDF]

Sensors (Basel), 2023
Huang YC, Hou CC.
europepmc   +1 more source

An investigation into in‐sample and out‐of‐sample model selection for nonstationary autoregressive models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract The stationary autoregressive model forms an important base of time‐series analysis in today's psychology research. Diverse nonstationary extensions of this model are developed to capture different types of changing temporal dynamics. However, researchers do not always have a solid theoretical base to rely on for deciding a‐priori which of ...
Yong Zhang, Anja F. Ernst, Ginette Lafit, Ward B. Eiling, Laura F. Bringmann   +4 more
wiley   +1 more source

Bregman–Hausdorff Divergence: Strengthening the Connections Between Computational Geometry and Machine Learning

Machine Learning and Knowledge Extraction
The purpose of this paper is twofold. On a technical side, we propose an extension of the Hausdorff distance from metric spaces to spaces equipped with asymmetric distance measures.
Tuyen Pham, Hana Dal Poz Kouřimská, Hubert Wagner   +2 more
doaj   +1 more source