A variable step implicit block multistep method for solving first-order ODEs. - Siamak Mehrkanoon; Zanariah Abdul Majid; Mohamed Suleiman (J. Comput. Appl. Math., 2010)

Symbolic computing of LS-SVM based models. - Siamak Mehrkanoon; Li Jiang; Carlos Alzate; Johan A. K. Suykens (ESANN, 2011)

A direct variable step block multistep method for solving general third-order ODEs. - Siamak Mehrkanoon (Numer. Algorithms, 2011)

LS-SVM approximate solution to linear time varying descriptor systems. - Siamak Mehrkanoon; Johan A. K. Suykens (Autom., 2012)

Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines. - Siamak Mehrkanoon; Tillmann Falck; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2012)

Non-parallel semi-supervised classification based on kernel spectral clustering. - Siamak Mehrkanoon; Johan A. K. Suykens (IJCNN, 2013)

Support vector machines with piecewise linear feature mapping. - Xiaolin Huang; Siamak Mehrkanoon; Johan A. K. Suykens (Neurocomputing, 2013)

SVD truncation schemes for fixed-size kernel models. - Ricardo Castro-Garcia; Siamak Mehrkanoon; Anna Marconato; Johan Schoukens; Johan A. K. Suykens (IJCNN, 2014)

Optimal reduced sets for sparse kernel spectral clustering. - Raghvendra Mall; Siamak Mehrkanoon; Rocco Langone; Johan A. K. Suykens (IJCNN, 2014)

Large scale semi-supervised learning using KSC based model. - Siamak Mehrkanoon; Johan A. K. Suykens (IJCNN, 2014)

Parameter estimation of delay differential equations: An integration-free LS-SVM approach. - Siamak Mehrkanoon; Saeid Mehrkanoon; Johan A. K. Suykens (Commun. Nonlinear Sci. Numer. Simul., 2014)

Non-parallel support vector classifiers with different loss functions. - Siamak Mehrkanoon; Xiaolin Huang; Johan A. K. Suykens (Neurocomputing, 2014)

Black-box modeling for temperature prediction in weather forecasting. - Zahra Karevan; Siamak Mehrkanoon; Johan A. K. Suykens (IJCNN, 2015)

Hierarchical semi-supervised clustering using KSC based model. - Siamak Mehrkanoon; Oscar Mauricio Agudelo; Raghvendra Mall; Johan A. K. Suykens (IJCNN, 2015)

Higher order Matching Pursuit for Low Rank Tensor Learning. - Yuning Yang; Siamak Mehrkanoon; Johan A. K. Suykens (CoRR, 2015)

Learning solutions to partial differential equations using LS-SVM. - Siamak Mehrkanoon; Johan A. K. Suykens (Neurocomputing, 2015)

Incremental multi-class semi-supervised clustering regularized by Kalman filtering. - Siamak Mehrkanoon; Oscar Mauricio Agudelo; Johan A. K. Suykens (Neural Networks, 2015)

Identifying intervals for hierarchical clustering using the Gershgorin circle theorem. - Raghvendra Mall; Siamak Mehrkanoon; Johan A. K. Suykens (Pattern Recognit. Lett., 2015)

Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering. - Siamak Mehrkanoon; Carlos Alzate; Raghvendra Mall; Rocco Langone; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2015)

Incorporation of Prior Knowledge into Kernel Based Models ; Incorporatie van voorkennis in kernel-gebaseerde modellen. - Siamak Mehrkanoon (2015)

Multi-label semi-supervised learning using regularized kernel spectral clustering. - Siamak Mehrkanoon; Johan A. K. Suykens (IJCNN, 2016)

Scalable Semi-supervised kernel spectral learning using random Fourier features. - Siamak Mehrkanoon; Johan A. K. Suykens (SSCI, 2016)

Estimating the unknown time delay in chemical processes. - Siamak Mehrkanoon; Yuri A. W. Shardt; Johan A. K. Suykens; Steven X. Ding (Eng. Appl. Artif. Intell., 2016)

Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses. - Yunlong Feng; Yuning Yang; Xiaolin Huang; Siamak Mehrkanoon; Johan A. K. Suykens (Neural Comput., 2016)

Scalable Hybrid Deep Neural Kernel Networks. - Siamak Mehrkanoon; Andreas Zell; Johan A. K. Suykens (ESANN, 2017)

Shallow and Deep Models for Domain Adaptation problems. - Siamak Mehrkanoon; Matthew B. Blaschko; Johan A. K. Suykens (ESANN, 2018)

Deep hybrid neural-kernel networks using random Fourier features. - Siamak Mehrkanoon; Johan A. K. Suykens (Neurocomputing, 2018)

Indefinite kernel spectral learning. - Siamak Mehrkanoon; Xiaolin Huang; Johan A. K. Suykens (Pattern Recognit., 2018)

Regularized Semipaired Kernel CCA for Domain Adaptation. - Siamak Mehrkanoon; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2018)

Deep shared representation learning for weather elements forecasting. - Siamak Mehrkanoon (Knowl. Based Syst., 2019)

Deep neural-kernel blocks. - Siamak Mehrkanoon (Neural Networks, 2019)

Cross-domain neural-kernel networks. - Siamak Mehrkanoon (Pattern Recognit. Lett., 2019)

A Real-time PCB Defect Detector Based on Supervised and Semi-supervised Learning. - Fan He; Sanli Tang; Siamak Mehrkanoon; Xiaolin Huang; Jie Yang 002 (ESANN, 2020)

Modelling human sound localization with deep neural networks. - Kiki van der Heijden; Siamak Mehrkanoon (ESANN, 2020)

Learning from partially labeled data. - Siamak Mehrkanoon; Xiaolin Huang; Johan A. K. Suykens (ESANN, 2020)

Wind speed prediction using multidimensional convolutional neural networks. - Kevin Trebing; Siamak Mehrkanoon (SSCI, 2020)

Deep brain state classification of MEG data. - Ismail Alaoui Abdellaoui; Jesús García Fernández; Caner Sahinli; Siamak Mehrkanoon (CoRR, 2020)

SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture. - Kevin Trebing; Siamak Mehrkanoon (CoRR, 2020)

Deep Neural-Kernel Machines. - Siamak Mehrkanoon (CoRR, 2020)

Deep multi-stations weather forecasting: explainable recurrent convolutional neural networks. - Ismail Alaoui Abdellaoui; Siamak Mehrkanoon (CoRR, 2020)

Deep coastal sea elements forecasting using U-Net based models. - Jesús García Fernández; Ismail Alaoui Abdellaoui; Siamak Mehrkanoon (CoRR, 2020)

Enhancing brain decoding using attention augmented deep neural networks. - Ismail Alaoui Abdellaoui; Jesús García Fernández; Caner Sahinli; Siamak Mehrkanoon (ESANN, 2021)

Deep Graph Convolutional Networks for Wind Speed Prediction. - Tomasz Stanczyk; Siamak Mehrkanoon (ESANN, 2021)

Exploring automatic liver tumor segmentation using deep learning. - Jesús García Fernández; Valerio Fortunati; Siamak Mehrkanoon (IJCNN, 2021)

Symbolic regression for scientific discovery: an application to wind speed forecasting. - Ismail Alaoui Abdellaoui; Siamak Mehrkanoon (SSCI, 2021)

Multistream Graph Attention Networks for Wind Speed Forecasting. - Dogan Aykas; Siamak Mehrkanoon (SSCI, 2021)

Towards biologically plausible learning in neural networks. - Jesús García Fernández; Enrique Hortal; Siamak Mehrkanoon (SSCI, 2021)

TENT: Tensorized Encoder Transformer for Temperature Forecasting. - Onur Bilgin; Pawel Maka; Thomas Vergutz; Siamak Mehrkanoon (CoRR, 2021)

Broad-UNet: Multi-scale feature learning for nowcasting tasks. - Jesús García Fernández; Siamak Mehrkanoon (Neural Networks, 2021)

SmaAt-UNet: Precipitation nowcasting using a small attention-UNet architecture. - Kevin Trebing; Tomasz Stanczyk; Siamak Mehrkanoon (Pattern Recognit. Lett., 2021)

AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks. - Yimin Yang; Siamak Mehrkanoon (IJCNN, 2022)

BAST: Binaural Audio Spectrogram Transformer for Binaural Sound Localization. - Sheng Kuang; Kiki van der Heijden; Siamak Mehrkanoon (CoRR, 2022)

GCN-FFNN: A two-stream deep model for learning solution to partial differential equations. - Onur Bilgin; Thomas Vergutz; Siamak Mehrkanoon (Neurocomputing, 2022)

Goal-driven, neurobiological-inspired convolutional neural network models of human spatial hearing. - Kiki van der Heijden; Siamak Mehrkanoon (Neurocomputing, 2022)

Deep coastal sea elements forecasting using UNet-based models. - Jesús García Fernández; Ismail Alaoui Abdellaoui; Siamak Mehrkanoon (Knowl. Based Syst., 2022)

SAR-UNet: Small Attention Residual UNet for Explainable Nowcasting Tasks. - Mathieu Renault; Siamak Mehrkanoon (IJCNN, 2023)

WF-UNet: Weather Data Fusion using 3D-UNet for Precipitation Nowcasting. - Christos Kaparakis; Siamak Mehrkanoon (INNS DLIA@IJCNN, 2023)

WF-UNet: Weather Fusion UNet for Precipitation Nowcasting. - Christos Kaparakis; Siamak Mehrkanoon (CoRR, 2023)

MSCDA: Multi-level semantic-guided contrast improves unsupervised domain adaptation for breast MRI segmentation in small datasets. - Sheng Kuang; Henry C. Woodruff; Renee Granzier; Thiemo J. A. van Nijnatten; Marc B. I. Lobbes; Marjolein L. Smidt; Philippe Lambin; Siamak Mehrkanoon (Neural Networks, 2023)

Dual Stream Graph Transformer Fusion Networks for Enhanced Brain Decoding. - Lucas Goené; Siamak Mehrkanoon (ESANN, 2024)

A novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classification. - Sergio Kazatzidis; Siamak Mehrkanoon (IJCNN, 2024)

GD-CAF: Graph Dual-stream Convolutional Attention Fusion for Precipitation Nowcasting. - Lorand Vatamany; Siamak Mehrkanoon (CoRR, 2024)

GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting. - Eloy Reulen; Siamak Mehrkanoon (CoRR, 2024)

Data-Efficient Sleep Staging with Synthetic Time Series Pretraining. - Niklas Grieger; Siamak Mehrkanoon; Stephan Bialonski (CoRR, 2024)

Self-supervised Spatial-Temporal Learner for Precipitation Nowcasting. - Haotian Li; Arno Siebes; Siamak Mehrkanoon (CoRR, 2024)

GA-SmaAt-GNet: Generative adversarial small attention GNet for extreme precipitation nowcasting. - Eloy Reulen; Jie Shi; Siamak Mehrkanoon (Knowl. Based Syst., 2024)

Graph Dual-stream Convolutional Attention Fusion for precipitation nowcasting. - Lorand Vatamany; Siamak Mehrkanoon (Eng. Appl. Artif. Intell., 2025)

TransCORALNet: A two-stream transformer CORAL networks for supply chain credit assessment cold start. - Jie Shi; Arno P. J. M. Siebes; Siamak Mehrkanoon (Expert Syst. Appl., 2025)

BAST-Mamba: Binaural Audio Spectrogram Mamba Transformer for binaural sound localization. - Sheng Kuang; Jie Shi; Kiki van der Heijden; Siamak Mehrkanoon (Neurocomputing, 2025)

Integrating Weather Station Data and Radar for Precipitation Nowcasting: SmaAt-fUsion and SmaAt-Krige-GNet. - Aleksej Cornelissen; Jie Shi; Siamak Mehrkanoon (CoRR, 2025)

SSA-UNet: Advanced Precipitation Nowcasting via Channel Shuffling. - Marco Turzi; Siamak Mehrkanoon (CoRR, 2025)

From Sleep Staging to Spindle Detection: Evaluating End-to-End Automated Sleep Analysis. - Niklas Grieger; Siamak Mehrkanoon; Philipp Ritter; Stephan Bialonski (CoRR, 2025)

Trans-XFed: An Explainable Federated Learning for Supply Chain Credit Assessment. - Jie Shi; Arno P. J. M. Siebes; Siamak Mehrkanoon (CoRR, 2025)