Results 91 to 100 of about 13,307,396 (304)
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
Learning Valued Relations from Data [PDF]
Driven by a large number of potential applications in areas like bioinformatics, information retrieval and social network analysis, the problem setting of inferring relations between pairs of data objects has recently been investigated quite intensively in the machine learning community.
Willem Waegeman +4 more
openaire +2 more sources
Mice can transfer the learned rule of spatial working memory to guide similar but novel tasks. Hippocampal CA3 populational activity dynamically reorganize during memory generalization, shifting from task‐specific to generalized coding over testing days. Sparse yet redundant neural representations of CA3 enable rule transfer and cognitive map formation,
Da Song +8 more
wiley +1 more source
Disaggregation of Bipolar-Valued Outranking Relations [PDF]
In this article, we tackle the problem of exploring the structure of the data which is underlying a bipolar-valued outranking relation. More precisely, we show how the performances of alternatives and weights related to criteria can be determined from three different formulations of the bipolar-valued outranking relations, which are given beforehand.
Meyer, Patrick +2 more
openaire +3 more sources
ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa +1 more
wiley +1 more source
Valuing birds: a quantitative approach to explore relational values
This study examines the concept of environmental relational values (RVs) by exploring the case of the human-nature relationships of birdwatchers. Because RVs are context-sensitive, they are difficult to capture quantitatively.
Zélie Stauffer +2 more
doaj +1 more source
GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin +1 more
wiley +1 more source
Exploring values, rules, and knowledge around traditional hunting in a rapidly developing society
Consideration of traditional practices of natural resource management in decision‐making is crucial to meet the challenges of the world’s intersecting sustainability crises.
Tobias Plieninger +6 more
doaj +1 more source
The ideas of relational values and social values are gaining prominence in sustainability science. Here, we ask: how well do these value conceptions resonate with one Indigenous worldview?
Rachelle K. Gould +3 more
semanticscholar +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source

