Results 231 to 240 of about 2,127,275 (322)
Abstract Research on the distributed practice effect, that is the impact of different intervals between learning sessions, has investigated both intentional and incidental learning of second language vocabulary and grammar targets. This research is complex and has produced conflicting findings: whereas robust effects have been shown for intentional ...
Shona Whyte +3 more
wiley +1 more source
privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images. [PDF]
Kim H, Kim M, Han B.
europepmc +1 more source
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Efficient numerical treatment of time fractional advection diffusion equations for modeling heat, pollutant and particle transport using subdivision collocation. [PDF]
Bibi S, Ejaz ST.
europepmc +1 more source
Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
wiley +1 more source
Quantum algorithms for equational reasoning. [PDF]
Rattacaso D +4 more
europepmc +1 more source
A Fast and Memory-Efficient Direct Rendering Method for Polynomial-Based Implicit Surfaces [PDF]
Jiayu Ren, Susumu Nakata
openalex +1 more source
Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor
ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
wiley +1 more source

