Analysis of Complex Systems Using the Self-Organizing Map. - Olli Simula; Esa Alhoniemi; Jaakko Hollmén; Juha Vesanto (ICONIP (2), 1997)

SOM Based Analysis of Pulping Process Data. - Olli Simula; Esa Alhoniemi (IWANN (2), 1999)

Process Monitoring and Modeling Using the Self-Organizing Map. - Esa Alhoniemi; Jaakko Hollmén; Olli Simula; Juha Vesanto (Integr. Comput. Aided Eng., 1999)

Clustering of the self-organizing map. - Juha Vesanto; Esa Alhoniemi (IEEE Trans. Neural Networks Learn. Syst., 2000)

Interpretation and comparison of multivariate data partitions. - Esa Alhoniemi; Olli Simula (ESANN, 2001)

Independent Variable Group Analysis. - Krista Lagus; Esa Alhoniemi; Harri Valpola (ICANN, 2001)

Unsupervised pattern recognition methods for exploratory analysis of industrial process data. - Esa Alhoniemi (2002)

Simplified time series representations for efficient analysis of industrial process data. - Esa Alhoniemi (Artif. Intell. Eng. Des. Anal. Manuf., 2003)

A Shape-Preserving Non-parametric Symmetry Transform. - Olli Lahdenoja; Esa Alhoniemi; Mika Laiho; Ari Paasio (ICPR (2), 2006)

Quantitation of the premature infant brain volume from MR images using watershed transform and Bayesian segmentation. - Harri Merisaari; Mika Teräs; Esa Alhoniemi; Riitta Parkkola; Olli S. Nevalainen (EUSIPCO, 2007)

Compact Modeling of Data Using Independent Variable Group Analysis. - Esa Alhoniemi; Antti Honkela; Krista Lagus; Santeri Jeremias Seppä; Paul Wagner; Harri Valpola (IEEE Trans. Neural Networks, 2007)

Agglomerative independent variable group analysis. - Antti Honkela; Jeremias Seppä; Esa Alhoniemi (Neurocomputing, 2008)

Adaptive Weight Aggregation in Federated Learning for Brain Tumor Segmentation. - Muhammad Irfan Khan; Mojtaba Jafaritadi; Esa Alhoniemi; Elina Kontio; Suleiman A. Khan (BrainLes@MICCAI (2), 2021)

Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation. - Muhammad Irfan Khan; Mohammad Ayyaz Azeem; Esa Alhoniemi; Elina Kontio; Suleiman A. Khan; Mojtaba Jafaritadi (BrainLes@MICCAI (2), 2022)

RegAgg: A Scalable Approach for Efficient Weight Aggregation in Federated Lesion Segmentation of Brain MRIs. - Muhammad Irfan Khan; Esa Alhoniemi; Elina Kontio; Suleiman A. Khan; Mojtaba Jafaritadi (FMEC, 2023)

Differential Privacy for Adaptive Weight Aggregation in Federated Tumor Segmentation. - Muhammad Irfan Khan; Esa Alhoniemi; Elina Kontio; Suleiman A. Khan; Mojtaba Jafaritadi (CoRR, 2023)