Results 141 to 150 of about 169,282 (318)
Bayesian Nonparametric Estimation and Consistency of Mixed Multinomial Logit Choice Models [PDF]
This paper develops nonparametric estimation for discrete choice models based on the Mixed Multinomial Logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models derived under the assumption of random utility maximization,
Lancelot F. James +2 more
core
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin +4 more
wiley +1 more source
Testing Nonlinear Logit Models of Performance Effectiveness Ratings: Cooperative Extension and Organic Farmers [PDF]
Survey evidence from U.S. organic farmers is evaluated to identify the factors influencing effectiveness ratings of cooperative extension advisors by organic farmers. A nonlinear logit model is specified for the ratings provided by organic producers, and
Lohr, Luanne, Park, Timothy A.
core
A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis
Advanced Intelligent Systems, EarlyView.METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen +3 more
wiley +1 more source
PMC11 WHICH ONE IS LOGICAL? LOGIT OR RARE EVENT LOGIT (RE-LOGIT)
Value in Health, 2005 Baser, O, Long, S
openaire +1 more source
Logit Models of Individual Choice
, 2008 The logit function is the reciprocal function to the sigmoid logistic function. It maps the interval [0,1] into the real line and is written as $$logit\left( p \right)=\ln \left( {p/\left( {1-p} \right)} \right).$$ (1) Two traditions are involved in the modern theory of logit models of individual choices.
openaire +3 more sources
Revista de la Facultad de Ciencias Agrarias, 2019 The aim of this paper is to develop a model of sustainable added value chain (SAVC). The model i) considers consumers expectations, ii) analyses the determinant producers´ factors to perform the SAVC and iii) ranks the agricultural subsectors according ...
Cristino Alberto Gómez-Luciano +3 more
doaj
Participation in Higher Education: A Random Parameter Logit Approach with Policy Simulations [PDF]
In this paper we present a theoretical model of higher education participation. We assume that young people that complete upper secondary education are faced with three choices, go to higher education, not go to higher education or go to higher education
O'Donoghue, Cathal, Flannery, Darragh
core
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