Search Results - Neural nets and related approaches to reference from stochastic processes

Towards end‐to‐end likelihood‐free inference with convolutional neural networks: Towards end-to-end likelihood-free inference with convolutional neural networks

Authors: Stefan T. Radev Ulf K. Mertens Andreas Voss et al.

Source: British Journal of Mathematical and Statistical Psychology. 73:23-43

Subject Terms: Likelihood Functions, Bayesian inference, 05 social sciences, leaky competing accumulator, Bayes Theorem, 01 natural sciences, Causal inference from observational studies, convolutional network, Neural nets and related approaches to inference from stochastic processes, Machine Learning, approximate Bayesian computation, machine learning, likelihood-free inference, Humans, Regression Analysis, Computer Simulation, 0501 psychology and cognitive sciences, Neural Networks, Computer, 0101 mathematics, Computational methods for problems pertaining to statistics, Algorithms, Applications of statistics to psychology

File Description: application/xml

Access URL: https://pubmed.ncbi.nlm.nih.gov/30793299
https://zbmath.org/7239909
https://doi.org/10.1111/bmsp.12159
https://www.onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12159
https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/bmsp.12159
https://www.ncbi.nlm.nih.gov/pubmed/30793299
https://pubmed.ncbi.nlm.nih.gov/30793299/
https://bpspsychub.onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12159
https://europepmc.org/article/MED/30793299

Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition.

Authors: Elbeltagi, Ahmed Katipoğlu, Okan Mert Kartal, Veysi et al.

Source: Applied Water Science; Dec2024, Vol. 14 Issue 12, p1-27, 27p

Subject Terms: HILBERT-Huang transform, OPTIMIZATION algorithms, SUSTAINABILITY, FARM management, BEES algorithm, WATERSHED management

Geographic Terms: EGYPT

Global stability conditions for delayed CNNs

Authors: Jinde Cao

Source: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications. 48:1330-1333

Subject Terms: Neural nets and related approaches to inference from stochastic processes, Qualitative investigation and simulation of models involving functional-differential equations, Stability theory of functional-differential equations, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, delayed cellular neural networks, 02 engineering and technology, Neural networks for/in biological studies, artificial life and related topics, 01 natural sciences, global stability

File Description: application/xml

Access URL: http://ieeexplore.ieee.org/document/964422
https://ieeexplore.ieee.org/document/964422/

Deep-learning-based automatic liver segmentation using computed tomography images in dogs.

Authors: Lee, Seungyeon Shimbo, Genya Yokoyama, Nozomu et al.

Source: Frontiers in Veterinary Science. 2025, p1-10. 10p.

Design and Implementation of a Deep Learning System to Analyze Bovine Sperm Morphology.

Authors: Sevilla, Francisco Araya-Zúñiga, Ignacio Méndez-Porras, Abel et al.

Source: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p1015. 18p.

Urbanization drives adaptive evolution in a Neotropical bird.

Authors: Mascarenhas, Rilquer Meirelles, Pedro Milet Batalha-Filho, Henrique

Source: Current Zoology. Oct2023, Vol. 69 Issue 5, p607-619. 13p.

Subjects: Biological evolution, Gene expression, City dwellers, Natural selection, Genetic regulation, Physiological adaptation, Bird populations

Geographic Terms: South America

Automated AI-based segmentation of canine hepatic focal lesions from CT studies.

Authors: Burti, Silvia Jurgas, Artur Puccinelli, Caterina et al.

Source: Frontiers in Veterinary Science. 2025, p1-9. 9p.

A Deep Learning Approach For Automated Rice Disease Detection And Classification.

Authors: Mandwariya, Deepika Jotwani, Varsha

Source: Journal of Advanced Zoology. 2024, Vol. 45 Issue 3, p316-335. 20p.

Ensemble Stochastic Configuration Networks for Estimating Prediction Intervals: A Simultaneous Robust Training Algorithm and Its Application.

Authors: Lu, Jun Ding, Jinliang Dai, Xuewu et al.

Source: IEEE Transactions on Neural Networks & Learning Systems; Dec2020, Vol. 31 Issue 12, p5426-5440, 15p

Subject Terms: FORECASTING, ALGORITHMS, STATISTICAL bootstrapping, MANUFACTURING processes, ACQUISITION of data, STOCHASTIC processes, OUTLIERS (Statistics)

Artificial Neural Network versus autoregressive approach: Prediction of total ozone time series.

Authors: Chattopadhyay, Surajit Chattopadhyay-Bandyopadhyay, Goutami

Source: Model Assisted Statistics & Applications; 2007, Vol. 2 Issue 3, p107-120, 14p, 1 Chart, 10 Graphs

Subject Terms: ARTIFICIAL neural networks, BACK propagation, AUTOREGRESSION (Statistics), ARTIFICIAL intelligence, MACHINE learning, STOCHASTIC processes

ENHANCING THE SUSTAINABILITY OF RABBIT PRODUCTION FROM THE PERSPECTIVE OF ANIMAL GENETICS.

Authors: Pablo Sánchez, Juan¹ juanpablo.sanchez@uco.es

Source: World Rabbit Science. Jan-Mar2025, Vol. 33 Issue 1, p1-11. 11p.

Development of a multicriteria decision-making model for evaluating hybrid offspring in the sweetpotato (Ipomoea batatas L.) breeding process.

Authors: Wei Xiang Kailong Li Fang Dong et al.

Source: Breeding Science. 2023, Vol. 73 Issue 3, p246-260. 15p.

Subjects: Sweet potatoes, Root growth, Decision making, Analytic hierarchy process, Sweetness (Taste), Multiple criteria decision making

Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Nutrition: A Systematic Review.

Authors: Theodore Armand, Tagne Poupi Nfor, Kintoh Allen Kim, Jung-In et al.

Source: Nutrients. Apr2024, Vol. 16 Issue 7, p1073. 24p.

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Authors: Tahghighi, Peyman Appleby, Ryan B. Norena, Nicole et al.

Source: Veterinary Radiology & Ultrasound. Jul2024, Vol. 65 Issue 4, p417-428. 12p.

YOLOv8-CBAM: a study of sheep head identification in Ujumqin sheep.

Authors: Qin, Qing Zhou, Xingyu Gao, Jiale et al.

Source: Frontiers in Veterinary Science. 2025, p1-10. 10p.

A benchmark for computational analysis of animal behavior, using animal-borne tags.

Authors: Hoffman, Benjamin Cusimano, Maddie Baglione, Vittorio et al.

Source: Movement Ecology. 12/18/2024, Vol. 12 Issue 1, p1-25. 25p.

PROCEEDINGS ONE HUNDRED AND TWENTY EIGHTH ANNUAL MEETING OF THE UNITED STATES ANIMAL HEALTH ASSOCIATION.

Source: Proceedings of the Annual Meeting of the United States Animal Health Association. 10/10/2024, Vol. 128, p1-339. 336p.

ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Mathematical modeling in ruminant nutrition: approaches and paradigms, extant models, and thoughts for upcoming predictive analytics^,.

Authors: Tedeschi, Luis O¹

Source: Journal of Animal Science. May2019, Vol. 97 Issue 5, p1921-1944. 24p.

Subjects: Artificial intelligence, Computer programming, Deep learning, Machine learning, Mathematical models, Simulation methods & models

Employing deep convolutional neural networks for segmenting the medial retropharyngeal lymph nodes in CT studies of dogs.

Authors: Schmid, David Scholz, Volkher B. Kircher, Patrick R. et al.

Source: Veterinary Radiology & Ultrasound. Nov2022, Vol. 63 Issue 6, p763-770. 8p.

Determination of Non-Digestible Parts in Dairy Cattle Feces Using U-NET and F-CRN Architectures.

Authors: Özden, Cevher Bulut, Mutlu Çanga Boğa, Demet et al.

Source: Veterinary Sciences. Jan2023, Vol. 10 Issue 1, p32. 14p.