Results 121 to 130 of about 719,028 (211)

Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels

, 2021
Prior works have found it beneficial to combine provably noise-robust loss functions e.g. mean absolute error (MAE) with standard categorical loss function e.g. crossentropy (CE) to improve their learnability.
Englesson, Erik, Azizpour, Hossein
core   +1 more source

An Active Sonar Signal Detection Algorithm Based on Weighted Neighbourhood Relative Entropy in the Underwater Acoustic Noise Environment

Journal of Marine Science and Engineering
This paper presents a target detection method for active sonar based on weighted neighbourhood relative entropy (WNRE), using tools from information geometry.
Ken Cheng, Jiaxi Cheng, Fangyong Wang, Xinyu Gu, Shuanping Du   +4 more
doaj   +1 more source

Understanding Risks in the Care of People With Dementia in Acute Hospital Settings: Definitions, Types and Management Strategies—A Scoping Review

Journal of Clinical Nursing, Volume 35, Issue 11, Page 4708-4724, November 2026.
ABSTRACT Aims This scoping review explores how risk is defined, managed and mitigated in the care of people with dementia in acute hospital settings. Methods This scoping review followed Arksesy and O'Malley's five‐stage framework (2005) and was guided by the Joanna Briggs Institute methodology.
Ashitha Bhaskaran, Kate Irving, Eileen Courtney, Bert Gordijn, Marie Cantwell   +4 more
wiley   +1 more source

Epistemic Capabilities of Artificial Intelligence for Public Administration and Policy Research: A Framework for Scholarship in the Age of Intelligent Machines

Policy Studies Journal, Volume 54, Issue 4, November 2026.
ABSTRACT Artificial intelligence (AI) has gained much interest in public administration and public policy fields in recent years. Research on and that uses AI has so far treated it as an object or context within the broader administrative and governance discourse.
Yanto Chandra, Jianxiang Tan
wiley   +1 more source

Heatmap showing the Jensen–Shannon (JS) divergence between challenge groups estimated from FPKM values for all genes.

, 2015
Heatmap showing the Jensen–Shannon (JS) divergence between challenge groups estimated from FPKM values for all genes.
Polyana C. Tizioto (762238), Christopher M. Seabury (194409), JaeWoo Kim (544072), Laurel J. Gershwin (653896), Rachel Toaff-Rosenstein (762239), Holly L. Neibergs (127865), Alison L. Van Eenennaam (242082), Robert D. Schnabel (194392), Jeremy F. Taylor (179789)   +8 more
core   +1 more source

Individual Brain Metabolic Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation Predicts Seizure Outcomes of Temporal Lobe Epilepsy. [PDF]

Front Cell Dev Biol, 2021
Zhu Z, Zhang Z, Gao X, Feng L, Chen D, Yang Z, Hu S.   +6 more
europepmc   +1 more source

Transfer‐Aided Deep Learning for Life Cycle Assessment Prediction of Precursor Molecules

ChemSusChem, Volume 19, Issue 19, 14 October 2026.
Transfer learning from commercial prices of molecules was found to increase the accuracy of machine learning models’ predictions of the environmental impacts of manufacturing simple organic molecules. This effect was verified for three separate model architectures. To date the environmental impacts of production of most chemicals are unknown, hindering
Michael Y. Zhou, Frank Roschangar, Fabian Stiefel, Philip Schulze, Alexei A. Lapkin   +4 more
wiley   +1 more source

A new method to measure the divergence in evidential sensor data fusion

International Journal of Distributed Sensor Networks, 2019
Evidence theory is widely used in real applications such as target recognition because of its efficiency in evidential sensor data fusing. However, counter-intuitive results may be obtained in the situation when evidence highly conflicts with each other.
Yutong Song, Yong Deng
doaj   +1 more source

Charting the Normal Development of Structural Brain Connectivity in Utero Using Diffusion MRI

Human Brain Mapping, Volume 47, Issue 14, October 1, 2026.
This study proposes new methods to study the development of the structural connectivity in utero using diffusion‐weighted MRI. The methods are applied on data from around 200 fetal brains to chart how the structural connectome develops between 22 and 37 gestational weeks.
Davood Karimi, Bo Li, Athena Taymourtash, Camilo Jaimes, P. Ellen Grant, Simon K. Warfield   +5 more
wiley   +1 more source

A Constrained‐Regression Machine Learning Model for Predicting Future Natural Land‐Cover Composition From Climate Projections

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Predicting future vegetation patterns from climate change projections is central to assessing ecological impacts, but most existing climate–vegetation models predict coarse biome classes rather than fine‐grained land cover. Here we develop a constrained regression approach that predicts local land cover composition (LLCC)—the fractional cover ...
T. F. Stepinski
wiley   +1 more source