Results 51 to 60 of about 2,463 (224)

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

open access: yesAdvanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu   +8 more
wiley   +1 more source

Abstract Representation of Movement Parameters in Basal Ganglia Output

open access: yesAdvanced Science, EarlyView.
The basal ganglia output provides a scalable velocity/position signal across behavioral contexts, supporting the idea that these variables are represented in the brain as abstract entities rather than as fixed changes in joint angles or specific sets of body effectors.
Ana Silvia Báez‐Cordero   +3 more
wiley   +1 more source

Hamiltonicity and pancyclicity of cartesian products of graphs

open access: yesDiscrete Mathematics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Roman Cada   +2 more
openaire   +3 more sources

qcGEM: A Graph‐Based Molecular Representation With Quantum Chemistry Awareness

open access: yesAdvanced Science, EarlyView.
In this work, we introduce qcGEM, a quantum‐chemistry‐aware graph‐based embedding of molecules that incorporates physical priors into molecular representation learning. Through a specially designed model architecture to adequately process quantum chemistry information as well as three‐dimensional molecular geometry, qcGEM provides a compact, physics ...
Haoyu Wang   +3 more
wiley   +1 more source

Graph decompositions for cartesian products

open access: yesElectronic Notes in Discrete Mathematics, 2005
Abstract In this paper we describe an algorithmic construction that, given a tree-decomposition of a graph G and a path-decomposition of a graph H , provides a tree-decomposition of the cartesian product of G and H . From the latter, we derive upper bounds on the treewidth and on the pathwidth of the cartesian product, expressed in terms of the
openaire   +1 more source

On the Crossing Numbers of Cartesian Products of Wheels and Trees

open access: yesDiscussiones Mathematicae Graph Theory, 2017
Bokal developed an innovative method for finding the crossing numbers of Cartesian product of two arbitrarily large graphs. In this article, the crossing number of the join product of stars and cycles are given.
Klešč Marián   +2 more
doaj   +1 more source

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

open access: yesAdvanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo   +4 more
wiley   +1 more source

Hamiltonicity of Cartesian products of graphs

open access: yesGraphs and Combinatorics
Abstract A path factor in a graph G is a factor of G in which every component is a path on at least two vertices. Let $$T\Box P_n$$
Irena Hrastnik Ladinek   +3 more
openaire   +2 more sources

Cartesian Products of Graphs and Metric Spaces

open access: yesEuropean Journal of Combinatorics, 2000
The authors give a short proof of the known fact that decomposition of a connected graph into a cartesian product of indecomposable factors is unique up to isomorphism. They then present a generalization of the results which shows uniqueness of decomposition for a wide class of product operations on general finite metric spaces.
Sergey V. Avgustinovich   +1 more
openaire   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

open access: yesAdvanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui   +4 more
wiley   +1 more source

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