Phoneme Recognition with Large Hierarchical Reservoirs. - Fabian Triefenbach; Azarakhsh Jalalvand; Benjamin Schrauwen; Jean-Pierre Martens (NIPS, 2010)

Discriminative transformation for speech features based on genetic algorithm and HMM likelihoods. - Behzad Zamani; Ahmad Akbari; Babak Nasersharif; Mehdi Mohammadi; Azarakhsh Jalalvand (IEICE Electron. Express, 2010)

Connected Digit Recognition by Means of Reservoir Computing. - Azarakhsh Jalalvand; Fabian Triefenbach; David Verstraeten; Jean-Pierre Martens (INTERSPEECH, 2011)

Optimized discriminative transformations for speech features based on minimum classification error. - Behzad Zamani; Ahmad Akbari; Babak Nasersharif; Azarakhsh Jalalvand (Pattern Recognit. Lett., 2011)

Continuous Digit Recognition in Noise: Reservoirs can do an excellent job! - Azarakhsh Jalalvand; Fabian Triefenbach; Jean-Pierre Martens (INTERSPEECH, 2012)

Context-dependent modeling and speaker normalization applied to reservoir-based phone recognition. - Fabian Triefenbach; Azarakhsh Jalalvand; Kris Demuynck; Jean-Pierre Martens (INTERSPEECH, 2013)

Noise robust continuous digit recognition with reservoir-based acoustic models. - Azarakhsh Jalalvand; Kris Demuynck; Jean-Pierre Martens (ISPACS, 2013)

Feature enhancement with a Reservoir-based Denoising Auto Encoder. - Azarakhsh Jalalvand; Kris Demuynck; Jean-Pierre Martens (ISSPIT, 2013)

Acoustic Modeling With Hierarchical Reservoirs. - Fabian Triefenbach; Azarakhsh Jalalvand; Kris Demuynck; Jean-Pierre Martens (IEEE Trans. Speech Audio Process., 2013)

Adaptive multicast routing method for 3D mesh-based Networks-on-Chip. - Poona Bahrebar; Azarakhsh Jalalvand; Dirk Stroobandt (SoCC, 2014)

Real-Time Reservoir Computing Network-Based Systems for Detection Tasks on Visual Contents. - Azarakhsh Jalalvand; Glenn Van Wallendael; Rik Van de Walle (CICSyN, 2015)

Robust continuous digit recognition using Reservoir Computing. - Azarakhsh Jalalvand; Fabian Triefenbach; Kris Demuynck; Jean-Pierre Martens (Comput. Speech Lang., 2015)

Towards using Reservoir Computing Networks for noise-robust image recognition. - Azarakhsh Jalalvand; Wesley De Neve; Rik Van de Walle; Jean-Pierre Martens (IJCNN, 2016)

An Automated End-To-End Pipeline for Fine-Grained Video Annotation using Deep Neural Networks. - Baptist Vandersmissen; Lucas Sterckx; Thomas Demeester; Azarakhsh Jalalvand; Wesley De Neve; Rik Van de Walle (ICMR, 2016)

Dynamically Reconfigurable Architecture for Fault-Tolerant 2D Networks-on-Chip. - Poona Bahrebar; Azarakhsh Jalalvand; Dirk Stroobandt (ICCCN, 2017)

Multivariate Time Series for Data-Driven Endpoint Prediction in the Basic Oxygen Furnace. - Davi Alberto Sala; Azarakhsh Jalalvand; Andy Van Yperen-De Deyne; Erik Mannens (ICMLA, 2018)

On the application of reservoir computing networks for noisy image recognition. - Azarakhsh Jalalvand; Kris Demuynck; Wesley De Neve; Jean-Pierre Martens (Neurocomputing, 2018)

Indoor Person Identification Using a Low-Power FMCW Radar. - Baptist Vandersmissen; Nicolas Knudde; Azarakhsh Jalalvand; Ivo Couckuyt; André Bourdoux; Wesley De Neve; Tom Dhaene (IEEE Trans. Geosci. Remote. Sens., 2018)

Multipitch tracking in music signals using Echo State Networks. - Peter Steiner; Simon Stone; Peter Birkholz; Azarakhsh Jalalvand (EUSIPCO, 2020)

Feature Engineering and Stacked Echo State Networks for Musical Onset Detection. - Peter Steiner; Azarakhsh Jalalvand; Simon Stone; Peter Birkholz (ICPR, 2020)

Indoor human activity recognition using high-dimensional sensors and deep neural networks. - Baptist Vandersmissen; Nicolas Knudde; Azarakhsh Jalalvand; Ivo Couckuyt; Tom Dhaene; Wesley De Neve (Neural Comput. Appl., 2020)

Unsupervised Pretraining of Echo State Networks for Onset Detection. - Peter Steiner; Azarakhsh Jalalvand; Peter Birkholz (ICANN (5), 2021)

Improved Acoustic Modeling for Automatic Piano Music Transcription Using Echo State Networks. - Peter Steiner; Azarakhsh Jalalvand; Peter Birkholz (IWANN (2), 2021)

PyRCN: Exploration and Application of ESNs. - Peter Steiner; Azarakhsh Jalalvand; Simon Stone; Peter Birkholz (CoRR, 2021)

Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems. - Utku Ozbulak; Baptist Vandersmissen; Azarakhsh Jalalvand; Ivo Couckuyt; Arnout Van Messem; Wesley De Neve (Comput. Vis. Image Underst., 2021)

PyRCN: A toolbox for exploration and application of Reservoir Computing Networks. - Peter Steiner; Azarakhsh Jalalvand; Simon Stone; Peter Birkholz (Eng. Appl. Artif. Intell., 2022)

Real-Time and Adaptive Reservoir Computing With Application to Profile Prediction in Fusion Plasma. - Azarakhsh Jalalvand; Joseph Abbate; Rory Conlin; Geert Verdoolaege; Egemen Kolemen (IEEE Trans. Neural Networks Learn. Syst., 2022)

Alfvén eigenmode detection using Long-Short Term Memory Networks and CO2 Interferometer data on the DIII-D National Fusion Facility. - Alvin V. Garcia; Azarakhsh Jalalvand; Peter Steiner; Andrew Rothstein; Michael Van Zeeland; William W. Heidbrink; Egemen Kolemen (IJCNN, 2023)

Application of neural networks in beam emission spectroscopy modelling. - Azarakhsh Jalalvand; Ors Asztalos; Mate Karacsonyi; Gergo I. Pokol (IJCNN, 2023)

Multimodal Prediction of Tearing Instabilities in a Tokamak. - Jaemin Seo; Rory Conlin; Andrew Rothstein; SangKyeun Kim; Joseph Abbate; Azarakhsh Jalalvand; Egemen Kolemen (IJCNN, 2023)

Non-Standard Echo State Networks for Video Door State Monitoring. - Peter Steiner; Azarakhsh Jalalvand; Peter Birkholz (IJCNN, 2023)

Hybrid static-sensory data modeling for prediction tasks in basic oxygen furnace process. - Davi Alberto Sala; Andy Van Yperen-De Deyne; Erik Mannens; Azarakhsh Jalalvand (Appl. Intell., 2023)

Cluster-Based Input Weight Initialization for Echo State Networks. - Peter Steiner; Azarakhsh Jalalvand; Peter Birkholz (IEEE Trans. Neural Networks Learn. Syst., 2023)

Exploring unsupervised pre-training for echo state networks. - Peter Steiner; Azarakhsh Jalalvand; Peter Birkholz (Neural Comput. Appl., 2023)

Diag2Diag: Multimodal super-resolution diagnostics for physics discovery with application to fusion. - Azarakhsh Jalalvand; Max Curie; SangKyeun Kim; Peter Steiner; Jaemin Seo; Qiming Hu; Andrew Oakleigh Nelson; Egemen Kolemen (CoRR, 2024)

Model-free stabilization via Extremum Seeking using a cost neural estimator. - Sara Dubbioso; Azarakhsh Jalalvand; Josiah Wai; Gianmaria De Tommasi; Egemen Kolemen (Expert Syst. Appl., 2024)

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements. - Kevin Gill; David R. Smith; Semin Joung; Benedikt Geiger; George McKee; J. Zimmerman; Ryan N. Coffee; Azarakhsh Jalalvand; Egemen Kolemen (Mach. Learn. Sci. Technol., 2024)

Avoiding fusion plasma tearing instability with deep reinforcement learning. - Jaemin Seo; SangKyeun Kim; Azarakhsh Jalalvand; Rory Conlin; Andrew Rothstein; Joseph Abbate; Keith Erickson; Josiah Wai; Ricardo Shousha; Egemen Kolemen (Nat., 2024)

Regulation Compliant AI for Fusion: Real-Time Image Analysis-Based Control of Divertor Detachment in Tokamaks. - Nathaniel Chen; Cheolsik Byun; Azarakhsh Jalalvand; SangKyeun Kim; Andrew Rothstein; Filippo Scotti; Steve Allen; David Eldon; Keith Erickson; Egemen Kolemen (CoRR, 2025)