Results 61 to 70 of about 1,258,420 (289)
Information Theoretic Causal Effect Quantification
Entropy, 2019 Modelling causal relationships has become popular across various disciplines. Most common frameworks for causality are the Pearlian causal directed acyclic graphs (DAGs) and the Neyman-Rubin potential outcome framework.
Aleksander Wieczorek, Volker Roth
doaj +1 more source
Directed Acyclic Graphs With Prototypical Networks for Few-Shot Emotion Recognition in Conversation
IEEE Access, 2023 Emotion recognition in conversation is the task of recognizing the emotion in each utterance of a conversation, and it is an active field of study with various applications.
Yujin Kang, Yoon-Sik Cho
doaj +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 +13 more
wiley +1 more source
The bayesvl package: An R package for implementing and visualizing Bayesian statistics
SoftwareX, 2022 The bayesvl R package implements Bayesian analysis using the Stan’s no-U-turn sampler (NUTS). Two distinguished functions that the bayesvl package complements to other developed packages and software performing Bayesian analysis are the “relationship ...
Viet-Phuong La +5 more
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Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
Advanced Intelligent Systems, EarlyView.A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Importance of directed acyclic graphs in medical education
Discover EducationMedical students are taught the importance of variable relationships in scientific research. We propose augmenting this education with teaching about direct acyclic graphs (DAGs)—a graphical model used to analyze complex systems of variables.
AlleaBelle Bradshaw, Jace C. Bradshaw
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Bayesian Network Learning with the PC Algorithm: An Improved and Correct Variation
Applied Artificial Intelligence, 2019 PC is a prototypical constraint-based algorithm for learning Bayesian networks, a special case of directed acyclic graphs. An existing variant of it, in the R package pcalg, was developed to make the skeleton phase order independent.
Michail Tsagris
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Causal Directed Acyclic Graphs [PDF]
JAMA, 2022 Ari M, Lipsky, Sander, Greenland
openaire +2 more sources
American Journal of Agricultural Economics, EarlyView.Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt +6 more
wiley +1 more source
Matching Directed Acyclic Graphs
, 2020 U ovom radu se bavimo problemom pronalaska maksimalnog sparivanja usmjerenih acikličkih grafova. Analizirat ćemo problem i prezentirat neke algoritme za rješavanje tog problema.In this paper we study the problem of finding maximum weight matching of ...
Blažević, Mislav
core +2 more sources