Results 61 to 70 of about 4,815 (240)
Advanced Intelligent Discovery, EarlyView.A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
, 2011 This thesis contains a discussion of four problems arising from the application of stochastic differential equations and real option theory to investment decision problems in a continuous-time framework.
Chavanasporn, Walailuck
core
Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
, 2011 Die Elektronisierung der Finanzmärkte ist in den letzten Jahren weit vorangeschritten. Praktisch jede Börse verfügt über ein elektronisches Handelssystem.
Gomolka, Johannes
core
Multi-Objective Genetic Programming-based Algorithmic Trading, using Directional Changes and a Modified Sharpe Ratio Score for Identifying Optimal Trading Strategies [PDF]
This study explores the integration of directional changes (DC), genetic programming (GP), and multi-objective optimisation (MOO) to develop advanced algorithmic trading strategies.
Long, Xinpeng +2 more
core +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Implementing and comparing various algorithmic trading strategies [PDF]
, 2018 Most financial firms use algorithms to buy and sell financial assets. It is possible for amateur investors with programming knowledge or vice-versa, to implement algorithms and improve their strategies.
Mc Laren, Eric
core
Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context
Agribusiness, EarlyView.
Alexis H. Villacis
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
Advanced Intelligent Discovery, EarlyView.This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source