Use of some sensitivity criteria for choosing networks with good generalization ability

Dimopoulos, Yannis, Bourret, Paul, Lek, Sovan·1995·Neural Processing Letters
DOI 10.1007/bf02309007

Cited by (267)

Items 201–267 of 267

  1. Dimension reduction and classification of hyperspectral images based on neural network sensitivity analysis and multi-instance learning
    Hui Liu, Chenming Li, Lizhong Xu · 2019 · Computer Science and Information Systems
  2. End-to-End Trained Sparse Coding Network with Spatial Pyramid Pooling for Image Classification
    Boheng Chen, Yige Wang, Gang Wei, Jie Li, Biyun Ma · 2019 · Neural Processing Letters
  3. An Application of Parametric and Nonparametric Models to the Assessment of Fluoride Levels in Vegetation Exposed to Stack Emissions of an Aluminum Reduction Plant in Greece
    Ioannis F. Dimopoulos, Ioannis X. Tsiros, Konstantinos Serelis, A. Kamoutsis, Aikaterini Chronopoulou · 2003 · Journal of the Air & Waste Management Association
  4. Deep Fundamental Factor Models
    Matthew Francis Dixon, Nicholas G. Polson · 2019 · arXiv (Cornell University)
  5. The Anatomy of Machine Learning-Based Portfolio Performance
    Philippe Goulet Coulombe, David E. Rapach, Erik Christian Montes Schütte, Sander Schwenk-Nebbe · 2023 · SSRN Electronic Journal
  6. Artificial neural network-driven self-calibrating model for thermodynamic analyses of advanced nuclear power plants
    Abid Hossain Khan, Farhan Fuad, Sk. Azmaeen Bin Amir, M. Sohel Rahman, Md Shafiqul Islam · 2025 · Progress in Nuclear Energy
  7. A Universal Approach to Mie Scatter Correction in FTIR Analysis of Microsized Samples
    Uladzislau Blazhko, Eirik Almklov Magnussen, Johanne Solheim, Simona Dzurendová, Volha Shapaval, Achim Köhler · 2025 · ACS Omega
  8. On the Granularity of Explanations in Model Agnostic NLP Interpretability
    Yves Rychener, Xavier Renard, Djamé Seddah, Pascal Frossard B, Marcin Detyniecki · 2023 · Communications in computer and information science
  9. Metric tools for sensitivity analysis with applications to neural networks
    Jaime Pizarroso Gonzalo, David Alfaya, José Portela, Antonio Muñoz · 2025 · Applied Soft Computing
  10. A non-linear Lasso and explainable LSTM approach for estimating tail risk interconnectedness
    Tuhin Subhra De, Madeti Karthikeya, Sujoy Bhattacharya · 2024 · Applied Economics
  11. GRAPHICAL REPRESENTATION OF CAUSE-EFFECT RELATIONSHIPS AMONG CHEMICAL PROCESS VARIABLES USING A NEURAL NETWORK APPROACH
    Gustavo Matheus de Almeida, Marcelo Cardoso, Danilo C. Rena, SONG W. PARK · 2010 · International Journal of Computational Intelligence and Applications
  12. Metric Tools for Sensitivity Analysis with Applications to Neural Networks
    Jaime Pizarroso Gonzalo, David Alfaya, José Portela, Antonio Muñoz San Roque · 2023
  13. Exploring the significance of temporal, meteorological, and previous states parameters in $$\hbox {PM}_{2.5}$$ concentration predictions: a neural network sensitivity study for Aguascalientes, Mexico
    Héctor Antonio Olmos-Guerrero, Pablo Tenoch Rodriguez-Gonzalez, Ramiro Rico-Martı́nez · 2025 · Modeling Earth Systems and Environment
  14. Artificial Intelligence For Air Quality Control Systems: A Holistic Approach
    Tony Bazzi, Mohamed Ali Zohdy · 2018 · International Middle East Power Systems Conference (MEPCON)
  15. Seleção de características de dados utilizando Redes Neurais Artificiais
    Álvaro Lima, Wilian Soares Lacerda, Heitor Scalco Neto · 2017 · Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI)
  16. Assessment of feature saliency of MLP using analytic sensitivity.
    Tommi Kärkkäinen · 2015 · The European Symposium on Artificial Neural Networks
  17. Modeling a Thermochemical Reactor of a Solar Refrigerator by BaCl2-NH3 Sorption Using Artificial Neural Networks and Mathematical Symmetry Groups
    Onésimo Meza-Cruz, I. Pilatowsky, Agustín Pérez-Ramírez, Carlos Rivera-Blanco, Youness El Hamzaoui, Miguel Pérez-Ramírez, Mauricio A. Sanchez · 2020 · Mathematical Problems in Engineering
  18. A novel approach for analyzing dynamics in neural networks with saturated characteristics
    Jianfeng Feng, David Brown · 1996 · Neural Processing Letters
  19. Habitat suitability models for the analysis and prediction of macrobenthos in the North Sea
    Wouter Willems · 2010 · Flanders Marine Institute (Flanders Marine Institute)
  20. Kernel Machines are Not Black Boxes - On the Interpretability of Kernel-based Nonparametric Models
    Billy Heung Wing Chang · 2014 · TSpace (University of Toronto)
  21. Sentence-Based Model Agnostic NLP Interpretability.
    Yves Rychener, Xavier Renard, Djamé Seddah, Pascal Frossard, Marcin Detyniecki · 2020 · arXiv (Cornell University)
  22. Feature Selection and Comparison of Logistic Regression and Random Forest for Stability Assessment of Landslide Dams
    He Fang, Fei Cai · 2025 · Landslides
  23. RETRACTED ARTICLE: Nonlinear interactions via machine learning: Input factor orchestration in sustainable operations
    Neil F. Johnson, Sameer Prasad, Rimi Zakaria, Amin Vahedian, Nezih Altay A · 2023 · Annals of Operations Research · Retracted
  24. Fragility Index: A New Approach for Binary Classification
    Chen Yang, Ziqiang Zhang, Bo Cao, Zheng Cui, B. Hu, Tongliang Li, Daniel Zhuoyu Long, Jin Qi, Feng Wang, Ruohan Zhan · 2023 · Knowledge Discovery and Data Mining
  25. Using Curves of Permanence to Study the Contribution of Input Variables in Artificial Neural Network Models: A New Proposed Methodology
    Havana Diogo Alves, Mêuser Valença · 2013 · BRICS Congress on Computational Intelligence and Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC)
  26. Extreme Latent Representation Learning for Visual Classification
    Tan Guo, Lei Zhang, Xiaoheng Tan · 2019 · Proceedings in adaptation, learning and optimization
  27. Stability Assessment Machine Learning Models Interpretation Based on Surrogate Models and Clustering
    Tiansen Han, Jinfu Chen, Yuyang Fu, Yanchun Cai, Shaofan Zhang · 2019 · IEEE Sustainable Power and Energy Conference (iSPEC)
  28. Real-Time Quality Monitoring and Diagnosis Using Convolutional Neural Network: An Application to the Pasting Process of Battery Manufacturing
    Yumin Liu, Zheyun Zhao, Yang Li · 2020 · Lecture notes in electrical engineering
  29. Parameter Sensitivity Analysis of Geotechnical Engineering System Using Neural Network Ensemble
    L.X. Pan, Y.R. Zhang, Maosen Cao, Drahomír Novák · 2015 · Advances in intelligent systems research/Advances in Intelligent Systems Research
  30. Modelling the long-term morphological evolution of tidal embayments
    Barend van Maanen · 2011 · Research Commons (University of Waikato)
  31. Human-grounded Evaluations of Explanation Methods for Text Classification
    Piyawat Lertvittayakumjorn, Francesca Toni · 2019 · arXiv (Cornell University)
  32. Non-linear Approach to Grouping, Dynamics and Organizational Informatics of Benthic Macroinvertebrate Communities in Streams by Artificial Neural Networks
    Tae‐Soo Chon, Y. S. Park, Ihn–Sil Kwak, E K E N N E D Y · 2003 · Springer eBooks
  33. Introducing ProsperNN—a Python package for forecasting with neural networks
    Nico Beck, Julia Schemm, Claudia Ehrig, Benedikt Sonnleitner, Ursula Neumann, Hans-Georg Zimmermann · 2024 · PeerJ Computer Science
  34. A review of model designs
    Piet F. M. Verdonschot, R.C. Nijboer · 2002 · Socio-Environmental Systems Modeling
  35. Model Selection: Selecting the Architecture of the Network
    Antonis Alexandridis, Achilleas D. Zapranis · 2014
  36. Variable Selection: Determining the Explanatory Variables
    Antonis Alexandridis, Achilleas D. Zapranis · 2014
  37. Viewing a class of neurodynamics on parameter space
    Jianfeng Feng, David Brown · 1997 · Lecture notes in computer science
  38. Factor Sensitivity Analysis for Multivariable Systems Using Bayesian Neural Networks
    Runbo Bai, Xiumei Qiu, Maosen Cao · 2009 · International Conference on Computational Intelligence and Security (CIS)
  39. Jacobian Neural Network Learning Algorithms
    André Elisseeff, Hélène Paugam‐Moisy · 1998 · Perspectives in neural computing
  40. Development of Artificial Intelligence Approach to Nowcasting and Forecasting Oyster Norovirus Outbreaks along the U.S. Gulf Coast
    Shima Shamkhali Chenar · 2017
  41. Using the Wide and Deep Flexible Neural Tree to Forecast the Exchange Rate
    Jing Xu, Peng Wu, Yuehui Chen, Hussain Dawood, Qingfei Meng · 2018 · Lecture notes in computer science
  42. Ecological Data Exploration
    Mohamed Elhadi Rahmani, Abdelmalek Amine · 2018 · Advances in computational intelligence and robotics book series
  43. Asset Pricing with Neural Networks: A Variable Significant Test
    Hasan A. Fallahgoul, Vincentius Franstianto · 2020 · SSRN Electronic Journal
  44. Detecting Preventable Disease Risk on Social Media
    Dane Bell · 2018 · UA Campus Repository (The University of Arizona)
  45. Spatial self-organization in Santiago: methods and applications.
    Raimundo Sánchez · 2021
  46. Beyond validation: assessing the legitimacy of artificial neural network models
    Humphrey, G., Holger Robert Maier, Wenyan Wu, Nick J. Mount, Graeme C. Dandy, Christian W. Dawson · 2021 · MODSIM
  47. References
    2021 · Emerald Group Publishing Limited eBooks
  48. Understanding the Uncertainty Using Sensitivity Analysis in Artificial Neural Networks
    Li Eckart, Margit Enke · 2022 · Developments in marketing science: proceedings of the Academy of Marketing Science
  49. Interpretability
    Matthew Francis Dixon, Igor Halperin, Paul Bilokon · 2020 · Springer eBooks
  50. Hierarchical Local Sensitivity Analysis Method for Optimization of Deep Learning-based Anomaly Detection in Communication Network
    Gang Yue, Zhuo Sun, Jinpo Fan · 2022 · IEEE/CIC International Conference on Communications in China (ICCC)
  51. Metric Tools for Sensitivity Analysis with Applications to Neural Networks
    Jaime Pizarroso Gonzalo, David Alfaya, José Portela, Antonio Muñoz San Roque · 2023
  52. Explore Unsupervised Structures in Pretrained Models for Relation Extraction
    Xi Yang, Tao Ji, Yuanbin Wu · 2022 · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)
  53. Evaluation of neural network attribution methods for microstructural representation of aero-engine material
    Xiaopeng Zhou · 2023 · Advances in Engineering Technology Research
  54. Predicting and Explaining Variations in Software Effort Estimation Using Adaptive Fuzzy-Neural Networks with Clustering
    Riyadh A. K. Mehdi · 2024 · Lecture notes in networks and systems
  55. Cohesive Attention-Based Explanations for Sequences and Explainability in Presence of Event Types
    Stephanie Ger, Yegna Subramanian Jambunath, Diego Klabjan, Jean Utke · 2023 · IEEE International Conference on Big Data (BigData)
  56. Simulation driven machine learning methods to optimise design of physical experiments and enhance data analysis for testing of fusion energy heat exchanger components
    Rhyd Lewis · 2024
  57. Evaporation Dynamics from the Perspective of High-Order Partial Deviations: A Case Study in Iran
    Mina Sayyah-Fard, Vahid Nourani, Yongqiang Zhang, Hüseyin Gökçekuş · 2024 · Environmental earth sciences
  58. Predictability and Complexity Dynamics in High-Frequency Financial Machine Learning
    Matthias Buchta · 2025 · SSRN Electronic Journal
  59. A Meta Learning Approach to Enhance Resolution in Uncertainty Space of Hydro- Climatic Artificial Intelligence Models
    Vahid Nourani, Mina Sayyah-Fard, Jinhui Jeanne Huang‬‬‬‬ · 2025 · Research Square
  60. Improved artificial neural network prediction of the pyrolysis behaviors of representative solid combustibles infiltrated with typical flammable liquids: an empirical study of Pinus sylvestris and kerosene
    Yixiang Wang, Ruiyu Chen, Yitao Liu, Yueqiang Wu, Ying Xu, Quanwei Li · 2025 · Thermal Science and Engineering Progress
  61. Feature Salience for Neural Networks: Comparing Algorithms
    Theodor Heinze, Martin von Löwis, Andreas Polze · 2012 · Lecture notes in computer science
  62. Dynamic modeling of PISA achievement scores: comparative analysis of artificial neural networks and differential equation systems approaches
    Bahatdin Daşbaşı · 2025 · Scientific Reports
  63. Machine Learning Meets Markowitz
    Yijie Wang, Hao Gao, Campbell R. Harvey, Yan Liu, Xinyuan Tao · 2025 · SSRN Electronic Journal
  64. Data-driven COD prediction during TiO 2 –P25 sonophotocatalysis of herbicide-contaminated wastewater: a neural-network benchmark
    Youness El Hamzaoui, Beatriz Fernanda Tejero Campos, Juan Antonio Álvarez-Arellano, Leonardo Palemón-Arcos, Homero Toral-Cruz, Luis Fernando Santis-Espinosa · 2026 · Chemical Product and Process Modeling
  65. Integrating GIS-based and AHP-enhanced approach for identifying earthquake zones in Northwest Vietnam
    Nguyen Manh Ha, Cao Dinh Trong, Cao Dinh Trieu, Duong Van Thanh, Nguyen Manh Luc, Mai Xuan Bach, Hoang Thi Huyen Ngoc, Nguyen Tien Thanh, Nguyen Thai Son · 2026 · Natural Hazards
  66. On the feasibility of machine-learning model for neutronic analyses of pressurized water reactor fuel assemblies
    Sayeed Anowar, Abid Hossain Khan, Md Mahfuzur Rahman, Md Tanbir Hasan, Md Waliuzzaman Talha, Md Shamim Hassan · 2026 · Nuclear Energy and Technology
  67. Untitled work
    2001 · 10.1577/1548-8659(2001)130