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Siamak Mehrkanoon
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2020 – today
- 2024
- [i23]Lorand Vatamany, Siamak Mehrkanoon:
GD-CAF: Graph Dual-stream Convolutional Attention Fusion for Precipitation Nowcasting. CoRR abs/2401.07958 (2024) - [i22]Eloy Reulen, Siamak Mehrkanoon:
GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting. CoRR abs/2401.09881 (2024) - [i21]Niklas Grieger, Siamak Mehrkanoon, Stephan Bialonski:
Data-Efficient Sleep Staging with Synthetic Time Series Pretraining. CoRR abs/2403.08592 (2024) - 2023
- [j25]Sheng Kuang, Henry C. Woodruff
, Renee Granzier, Thiemo J. A. van Nijnatten, Marc B. I. Lobbes, Marjolein L. Smidt, Philippe Lambin, Siamak Mehrkanoon
:
MSCDA: Multi-level semantic-guided contrast improves unsupervised domain adaptation for breast MRI segmentation in small datasets. Neural Networks 165: 119-134 (2023) - [c26]Mathieu Renault, Siamak Mehrkanoon
:
SAR-UNet: Small Attention Residual UNet for Explainable Nowcasting Tasks. IJCNN 2023: 1-8 - [c25]Christos Kaparakis, Siamak Mehrkanoon:
WF-UNet: Weather Data Fusion using 3D-UNet for Precipitation Nowcasting. INNS DLIA@IJCNN 2023: 223-232 - [i20]Sheng Kuang, Henry C. Woodruff, Renee Granzier, Thiemo J. A. van Nijnatten, Marc B. I. Lobbes, Marjolein L. Smidt, Philippe Lambin, Siamak Mehrkanoon:
MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasets. CoRR abs/2301.02554 (2023) - [i19]Christos Kaparakis, Siamak Mehrkanoon:
WF-UNet: Weather Fusion UNet for Precipitation Nowcasting. CoRR abs/2302.04102 (2023) - [i18]Mathieu Renault, Siamak Mehrkanoon:
SAR-UNet: Small Attention Residual UNet for Explainable Nowcasting Tasks. CoRR abs/2303.06663 (2023) - [i17]Jie Shi, Arno P. J. M. Siebes, Siamak Mehrkanoon:
TransCORALNet: A Two-Stream Transformer CORAL Networks for Supply Chain Credit Assessment Cold Start. CoRR abs/2311.18749 (2023) - [i16]Sergio Kazatzidis, Siamak Mehrkanoon:
A novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classification. CoRR abs/2312.09623 (2023) - 2022
- [j24]Kiki van der Heijden, Siamak Mehrkanoon
:
Goal-driven, neurobiological-inspired convolutional neural network models of human spatial hearing. Neurocomputing 470: 432-442 (2022) - [j23]Onur Bilgin, Thomas Vergutz
, Siamak Mehrkanoon
:
GCN-FFNN: A two-stream deep model for learning solution to partial differential equations. Neurocomputing 511: 131-141 (2022) - [j22]Jesús García Fernández, Ismail Alaoui Abdellaoui, Siamak Mehrkanoon
:
Deep coastal sea elements forecasting using UNet-based models. Knowl. Based Syst. 252: 109445 (2022) - [c24]Yimin Yang, Siamak Mehrkanoon
:
AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks. IJCNN 2022: 1-8 - [i15]Yimin Yang, Siamak Mehrkanoon:
AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks. CoRR abs/2202.04996 (2022) - [i14]Onur Bilgin, Thomas Vergutz, Siamak Mehrkanoon:
GCN-FFNN: A Two-Stream Deep Model for Learning Solution to Partial Differential Equations. CoRR abs/2204.13744 (2022) - [i13]Sheng Kuang, Kiki van der Heijden, Siamak Mehrkanoon
:
BAST: Binaural Audio Spectrogram Transformer for Binaural Sound Localization. CoRR abs/2207.03927 (2022) - 2021
- [j21]Jesús García Fernández, Siamak Mehrkanoon
:
Broad-UNet: Multi-scale feature learning for nowcasting tasks. Neural Networks 144: 419-427 (2021) - [j20]Kevin Trebing, Tomasz Stanczyk, Siamak Mehrkanoon
:
SmaAt-UNet: Precipitation nowcasting using a small attention-UNet architecture. Pattern Recognit. Lett. 145: 178-186 (2021) - [c23]Ismail Alaoui Abdellaoui, Jesús García Fernández, Caner Sahinli, Siamak Mehrkanoon
:
Enhancing brain decoding using attention augmented deep neural networks. ESANN 2021 - [c22]Tomasz Stanczyk, Siamak Mehrkanoon
:
Deep Graph Convolutional Networks for Wind Speed Prediction. ESANN 2021 - [c21]Jesús García Fernández, Valerio Fortunati, Siamak Mehrkanoon
:
Exploring automatic liver tumor segmentation using deep learning. IJCNN 2021: 1-8 - [c20]Ismail Alaoui Abdellaoui, Siamak Mehrkanoon
:
Symbolic regression for scientific discovery: an application to wind speed forecasting. SSCI 2021: 1-8 - [c19]Dogan Aykas, Siamak Mehrkanoon
:
Multistream Graph Attention Networks for Wind Speed Forecasting. SSCI 2021: 1-8 - [c18]Jesús García Fernández, Enrique Hortal
, Siamak Mehrkanoon
:
Towards biologically plausible learning in neural networks. SSCI 2021: 1-8 - [i12]Tomasz Stanczyk, Siamak Mehrkanoon:
Deep Graph Convolutional Networks for Wind Speed Prediction. CoRR abs/2101.10041 (2021) - [i11]Jesús García Fernández, Siamak Mehrkanoon:
Broad-UNet: Multi-scale feature learning for nowcasting tasks. CoRR abs/2102.06442 (2021) - [i10]Ismail Alaoui Abdellaoui, Siamak Mehrkanoon:
Symbolic regression for scientific discovery: an application to wind speed forecasting. CoRR abs/2102.10570 (2021) - [i9]Onur Bilgin, Pawel Maka, Thomas Vergutz, Siamak Mehrkanoon:
TENT: Tensorized Encoder Transformer for Temperature Forecasting. CoRR abs/2106.14742 (2021) - [i8]Dogan Aykas, Siamak Mehrkanoon:
Multistream Graph Attention Networks for Wind Speed Forecasting. CoRR abs/2108.07063 (2021) - 2020
- [c17]Siamak Mehrkanoon, Xiaolin Huang, Johan A. K. Suykens:
Learning from partially labeled data. ESANN 2020: 493-502 - [c16]Kiki van der Heijden, Siamak Mehrkanoon:
Modelling human sound localization with deep neural networks. ESANN 2020: 521-526 - [c15]Fan He, Sanli Tang, Siamak Mehrkanoon, Xiaolin Huang, Jie Yang:
A Real-time PCB Defect Detector Based on Supervised and Semi-supervised Learning. ESANN 2020: 527-532 - [c14]Kevin Trebing, Siamak Mehrkanoon
:
Wind speed prediction using multidimensional convolutional neural networks. SSCI 2020: 713-720 - [i7]Ismail Alaoui Abdellaoui, Jesús García Fernández, Caner Sahinli, Siamak Mehrkanoon:
Deep brain state classification of MEG data. CoRR abs/2007.00897 (2020) - [i6]Kevin Trebing, Siamak Mehrkanoon:
SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture. CoRR abs/2007.04417 (2020) - [i5]Siamak Mehrkanoon:
Deep Neural-Kernel Machines. CoRR abs/2007.06655 (2020) - [i4]Kevin Trebing, Siamak Mehrkanoon:
Wind speed prediction using multidimensional convolutional neural networks. CoRR abs/2007.12567 (2020) - [i3]Ismail Alaoui Abdellaoui, Siamak Mehrkanoon:
Deep multi-stations weather forecasting: explainable recurrent convolutional neural networks. CoRR abs/2009.11239 (2020) - [i2]Jesús García Fernández, Ismail Alaoui Abdellaoui, Siamak Mehrkanoon:
Deep coastal sea elements forecasting using U-Net based models. CoRR abs/2011.03303 (2020)
2010 – 2019
- 2019
- [j19]Siamak Mehrkanoon
:
Deep shared representation learning for weather elements forecasting. Knowl. Based Syst. 179: 120-128 (2019) - [j18]Siamak Mehrkanoon
:
Deep neural-kernel blocks. Neural Networks 116: 46-55 (2019) - [j17]Siamak Mehrkanoon
:
Cross-domain neural-kernel networks. Pattern Recognit. Lett. 125: 474-480 (2019) - [c13]Siamak Mehrkanoon:
Cross-Domain Neural-Kernel Networks. BNAIC/BENELEARN 2019 - [c12]Siamak Mehrkanoon:
Deep Shared Representation Learning for Weather Elements Forecasting. BNAIC/BENELEARN 2019 - 2018
- [j16]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Deep hybrid neural-kernel networks using random Fourier features. Neurocomputing 298: 46-54 (2018) - [j15]Siamak Mehrkanoon
, Xiaolin Huang
, Johan A. K. Suykens
:
Indefinite kernel spectral learning. Pattern Recognit. 78: 144-153 (2018) - [j14]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Regularized Semipaired Kernel CCA for Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3199-3213 (2018) - [c11]Siamak Mehrkanoon, Matthew B. Blaschko, Johan A. K. Suykens:
Shallow and Deep Models for Domain Adaptation problems. ESANN 2018 - 2017
- [c10]Siamak Mehrkanoon, Andreas Zell, Johan A. K. Suykens:
Scalable Hybrid Deep Neural Kernel Networks. ESANN 2017 - 2016
- [j13]Siamak Mehrkanoon
, Yuri A. W. Shardt
, Johan A. K. Suykens
, Steven X. Ding:
Estimating the unknown time delay in chemical processes. Eng. Appl. Artif. Intell. 55: 219-230 (2016) - [j12]Yunlong Feng, Yuning Yang, Xiaolin Huang, Siamak Mehrkanoon
, Johan A. K. Suykens
:
Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses. Neural Comput. 28(6): 1217-1247 (2016) - [c9]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Multi-label semi-supervised learning using regularized kernel spectral clustering. IJCNN 2016: 4009-4016 - [c8]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Scalable Semi-supervised kernel spectral learning using random Fourier features. SSCI 2016: 1-8 - 2015
- [b1]Siamak Mehrkanoon:
Incorporation of Prior Knowledge into Kernel Based Models ; Incorporatie van voorkennis in kernel-gebaseerde modellen. Katholieke Universiteit Leuven, Belgium, 2015 - [j11]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Learning solutions to partial differential equations using LS-SVM. Neurocomputing 159: 105-116 (2015) - [j10]Siamak Mehrkanoon
, Oscar Mauricio Agudelo, Johan A. K. Suykens
:
Incremental multi-class semi-supervised clustering regularized by Kalman filtering. Neural Networks 71: 88-104 (2015) - [j9]Raghvendra Mall
, Siamak Mehrkanoon
, Johan A. K. Suykens
:
Identifying intervals for hierarchical clustering using the Gershgorin circle theorem. Pattern Recognit. Lett. 55: 1-7 (2015) - [j8]Siamak Mehrkanoon
, Carlos Alzate, Raghvendra Mall
, Rocco Langone
, Johan A. K. Suykens
:
Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering. IEEE Trans. Neural Networks Learn. Syst. 26(4): 720-733 (2015) - [c7]Zahra Karevan, Siamak Mehrkanoon
, Johan A. K. Suykens
:
Black-box modeling for temperature prediction in weather forecasting. IJCNN 2015: 1-8 - [c6]Siamak Mehrkanoon
, Oscar Mauricio Agudelo, Raghvendra Mall
, Johan A. K. Suykens
:
Hierarchical semi-supervised clustering using KSC based model. IJCNN 2015: 1-8 - [i1]Yuning Yang, Siamak Mehrkanoon, Johan A. K. Suykens:
Higher order Matching Pursuit for Low Rank Tensor Learning. CoRR abs/1503.02216 (2015) - 2014
- [j7]Siamak Mehrkanoon
, Saeid Mehrkanoon, Johan A. K. Suykens
:
Parameter estimation of delay differential equations: An integration-free LS-SVM approach. Commun. Nonlinear Sci. Numer. Simul. 19(4): 830-841 (2014) - [j6]Siamak Mehrkanoon
, Xiaolin Huang, Johan A. K. Suykens
:
Non-parallel support vector classifiers with different loss functions. Neurocomputing 143: 294-301 (2014) - [c5]Raghvendra Mall
, Siamak Mehrkanoon
, Rocco Langone
, Johan A. K. Suykens
:
Optimal reduced sets for sparse kernel spectral clustering. IJCNN 2014: 2436-2443 - [c4]Ricardo Castro-Garcia, Siamak Mehrkanoon
, Anna Marconato, Johan Schoukens, Johan A. K. Suykens:
SVD truncation schemes for fixed-size kernel models. IJCNN 2014: 3922-3929 - [c3]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Large scale semi-supervised learning using KSC based model. IJCNN 2014: 4152-4159 - 2013
- [j5]Xiaolin Huang, Siamak Mehrkanoon
, Johan A. K. Suykens
:
Support vector machines with piecewise linear feature mapping. Neurocomputing 117: 118-127 (2013) - [c2]Siamak Mehrkanoon
, Johan A. K. Suykens
:
Non-parallel semi-supervised classification based on kernel spectral clustering. IJCNN 2013: 1-8 - 2012
- [j4]Siamak Mehrkanoon
, Johan A. K. Suykens
:
LS-SVM approximate solution to linear time varying descriptor systems. Autom. 48(10): 2502-2511 (2012) - [j3]Siamak Mehrkanoon
, Tillmann Falck, Johan A. K. Suykens
:
Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 23(9): 1356-1367 (2012) - 2011
- [j2]Siamak Mehrkanoon
:
A direct variable step block multistep method for solving general third-order ODEs. Numer. Algorithms 57(1): 53-66 (2011) - [c1]Siamak Mehrkanoon, Li Jiang, Carlos Alzate, Johan A. K. Suykens:
Symbolic computing of LS-SVM based models. ESANN 2011 - 2010
- [j1]Siamak Mehrkanoon
, Zanariah Abdul Majid, Mohamed Suleiman:
A variable step implicit block multistep method for solving first-order ODEs. J. Comput. Appl. Math. 233(9): 2387-2394 (2010)
Coauthor Index
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last updated on 2024-06-10 20:28 CEST by the dblp team
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