Results 241 to 250 of about 783,181 (348)

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

The Role of Sodium Cations and Covalent Decoration in the Dissociation of Supramolecular Polymers and a Rational Strategy to Improve Their Stability. [PDF]

Chemistry
Petelski AN, Gómez Chávez JL, Zalazar LR, Miranda MO.   +3 more
europepmc   +1 more source

PERFECT PAIRS OF TREES IN GRAPHS

No author provided
openalex   +1 more source

The P-vertex problem for graphs with perfect matchings [PDF]

G. Arunkumar, U. S. Jerisha
openalex   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source

A PERFECT-SET VAUGHT DICHOTOMY FOR COUNTABLE BICONNECTED K4-MINOR-FREE GRAPHS

Yueer Yang
openalex   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

Correction for Lee et al., Emergence of a contrast-invariant representation of naturalistic texture in macaque visual cortex. [PDF]

Proc Natl Acad Sci U S A
europepmc   +1 more source

Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms. [PDF]

Philos Trans A Math Phys Eng Sci
Minenkova A, Mograby G, Zhan H.
europepmc   +1 more source

On some perfect matching conjectures in infinite, cubic, bridgeless graphs [PDF]

Paulo Magalhães Júnior, Antônio Kelson Silva   +1 more
openalex   +1 more source