Results 91 to 100 of about 416,031 (239)
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Content and Epistemic Relations: A Developmental Study of Recall
The study investigates the types of coherence relations adults and children can recall after having read a text. We discerned content and epistemic relations (Dancygier, 1998; Sweetser, 1990). Content relations express relations between events in reality.
Sara Verbrugge, Aline Sevenants
doaj +1 more source
Temporal Relations: Reference or Discourse Coherence?
The temporal relations that hold between events described by successive utterances are often left implicit or underspecified. We address the role of two phenomena with respect to the recovery of these relations: (1) the referential properties of tense ...
Kehler, Andrew
core +2 more sources
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Introduction Discourse coherence refers to the semantic connectedness of propositions in a connected speech. Various theoretical bases, narrative elicitation tasks, and sample quantifications as well as small sample sizes in most studies resulted in a ...
Anthony Pak Hin Kong +3 more
doaj +1 more source
Finding coherence between EU concentrations-related instruments [PDF]
Item does not contain ...
openaire +4 more sources
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 +4 more
wiley +1 more source
The malfunctioning of the brain synucleins is associated with pathogenesis of Parkinson’s disease. Synucleins’ ability to modulate various pre-synaptic processes suggests their modifying effects on the electroencephalogram (EEG) recorded from different ...
Vasily Vorobyov +3 more
doaj +1 more source
Minimum uncertainty solutions for partially coherent fields and quantum mixed states
A general prescription is given for finding uncertainty relations that dictate the lower bounds on the measures of spread corresponding to two different representations of a partially coherent wave field or mixed quantum state, for a given measure of ...
M Alonso, T Setälä, A T Friberg
doaj +1 more source
Musculoskeletal humanoids exhibit rich biomechanical properties that remain insufficiently unified in prior discussions. This article systematically categorizes muscle characteristics into five properties: redundancy, independency, anisotropy, variable moment arm, and nonlinear elasticity, and analyzes their combined effects on control.
Kento Kawaharazuka +2 more
wiley +1 more source

