Results 71 to 80 of about 776 (171)

Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?

Applied Stochastic Models in Business and Industry, Volume 41, Issue 2, March/April 2025.
ABSTRACT The paper arises from the experience of Applied Stochastic Models in Business and Industry which has seen, over the years, more and more contributions related to Machine Learning rather than to what was intended as a stochastic model. The very notion of a stochastic model (e.g., a Gaussian process or a Dynamic Linear Model) can be subject to ...
Fabrizio Ruggeri, David Banks, William S. Cleveland, Nicholas I. Fisher, Marcos Escobar‐Anel, Paolo Giudici, Emanuela Raffinetti, Roger W. Hoerl, Dennis K. J. Lin, Ron S. Kenett, Wai Keung Li, Philip L. H. Yu, Jean‐Michel Poggi, Marco S. Reis, Gilbert Saporta, Piercesare Secchi, Rituparna Sen, Ansgar Steland, Zhanpan Zhang   +18 more
wiley   +1 more source

Scaling Laws for Discriminative Classification in Large Language Models

Applied AI Letters, Volume 6, Issue 1, February 2025.
ABSTRACT Modern large language models (LLMs) represent a paradigm shift in what can plausibly be expected of machine learning models. The fact that LLMs can effectively generate sensible answers to a diverse range of queries suggests that they would be useful in customer support applications.
Dean Wyatte, Fatemeh Tahmasbi, Ming Li, Thomas Markovich   +3 more
wiley   +1 more source

Improving Empirical Pressure Estimation Over Mainland China and Surrounding Regions Using Machine Learning

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Accurate pressure is required in high-precision geodetic applications, including global navigation satellite systems (GNSS) and very long baseline interferometry (VLBI). Widely used empirical models provide pressure estimates from location and time alone,
Liying Cao, Junyu Li, Baoshuang Zhang, Lilong Liu, Bao Zhang, Yibin Yao, Liangke Huang   +6 more
doaj   +1 more source

"Künstliche Intelligenz" à la GPT3: Die große Remix-Maschine

, 2023
GPT3 ist eine Software, mit der sich wie von Zauberhand Texte erstellen lassen. Das Etikett "Künstliche Intelligenz" dürfte trotz aller Hoffnungen zu hoch gegriffen sein. Denn GPT3 erzeugt vor allem Remixes von bestehenden Texten. Wie lernt die Maschine zu schreiben? Und ist die neue Technologie Fluch oder Segen für die Kreativbranche?
openaire   +1 more source

You're (Not) My Type‐ Can LLMs Generate Feedback of Specific Types for Introductory Programming Tasks?

Journal of Computer Assisted Learning, Volume 41, Issue 1, February 2025.
ABSTRACT Background Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience.
Dominic Lohr, Hieke Keuning, Natalie Kiesler   +2 more
wiley   +1 more source

Integrating Human Expert Knowledge with OpenAI and ChatGPT: A Secure and Privacy-Enabled Knowledge Acquisition Approach [PDF]

, 2023
Advanced Large Language Models (LLMs) struggle to produce accurate results and preserve user privacy for use cases involving domain-specific knowledge.
Phillips, Ben
core  

Deep Neural Networks for Refining Vertical Modeling of Global Tropospheric Delay

Geophysical Research Letters, Volume 52, Issue 2, 28 January 2025.
Abstract Kinematic airborne platforms are becoming increasingly vital for Earth observation. They highlight the critical need for accurate tropospheric delay corrections across varying altitudes, especially as most existing models are limited to Earth's surface.
Peng Yuan, Kyriakos Balidakis, Jungang Wang, Pengfei Xia, Jian Wang, Mingyuan Zhang, Weiping Jiang, Harald Schuh, Jens Wickert, Zhiguo Deng   +9 more
wiley   +1 more source

How the technologies behind self‐driving cars, social networks, ChatGPT, and DALL‐E2 are changing structural biology

BioEssays, Volume 47, Issue 1, January 2025.
Deep learning, a brain inspired field of computer science, revolutionizes structural biology. I summarize how convolutional neural networks (CNNs), large language models (LLMs), denoising diffusion probabilistic models (DDPMs)/Noise conditional score networks (NCSNs), and graph neural networks (GNNs) have impacted protein structure prediction, inverse ...
Matthias Bochtler
wiley   +1 more source

Participación de epítopos de reconocimiento de linfocitos t de la proteína GP5 del virus PRRSV en la respuesta inmune innata porcina [PDF]

, 2023
Instituto de Investigaciones Agropecuarias y Forestales. Facultad de Biología. Facultad de Medicina Veterinaria y Zootecnia. Facultad de Agrobiología. Facultad de Químico Farmacobiología.
Roberto Ortega Flores
core  

Utilizing large language models for EFL essay grading: An examination of reliability and validity in rubric‐based assessments

British Journal of Educational Technology, Volume 56, Issue 1, Page 150-166, January 2025.
Abstract This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student
Fatih Yavuz, Özgür Çelik, Gamze Yavaş Çelik   +2 more
wiley   +1 more source