Results 81 to 90 of about 17,065,182 (226)

Multinomial Logit Models with Implicit Variable Selection [PDF]

, 2010
Multinomial logit models which are most commonly used for the modeling of unordered multi-category responses are typically restricted to the use of few predictors. In the high-dimensional case maximum likelihood estimates frequently do not exist. In this
Tutz, Gerhard, Zahid, Faisal Maqbool
core   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Protein sequence classification using natural language processing techniques

Discover Artificial Intelligence
Purpose This study aimed to enhance protein sequence classification using natural language processing (NLP) techniques while addressing the impact of sequence similarity on model performance.
Huma Perveen, Julie Weeds
doaj   +1 more source

Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays

Advanced Intelligent Systems, EarlyView.
This work develops a sheet made with arrays of soft optical fibers that can reconstruct its 3D surface shape. Synergy of the waveguides’ responses to bending and pressing force allows shape reconstruction with resilience to damage. Applied onto surfaces of robotic or living systems, our design can be implemented in virtual reality, teleoperation ...
Qifan Yu, Nina Cao, Kaitlyn Becker
wiley   +1 more source

MNP: R Package for Fitting the Multinomial Probit Model [PDF]

MNP is a publicly available R package that fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the
Kosuke Imai, David A. Van Dyk
core  

Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science

Advanced Intelligent Systems, EarlyView.
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska, Joanna Neubauer, Monika Sztuder, Witold Taisner, Agnieszka Hryniewicka, Julia Kolodziejczyk, Marta Eliza Plonska‐Brzezinska, Dariusz Brzezinski   +7 more
wiley   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Simulated z-tests in multinomial probit models [PDF]

Within the framework of Monte Carlo experiments, this paper systematically compares different versions of the simulated z-test (using the GHK simulator) in one- and multiperiod multinomial probit models.
Ziegler, Andreas
core  

Data_Sheet_1_Testing Interactions in Multinomial Processing Tree Models.zip

, 2019
Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects.
Beatrice G. Kuhlmann (7616789), Morten Moshagen (7616795), Edgar Erdfelder (7616792)   +2 more
core   +1 more source