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ORCIDAzarakhsh Jalalvand
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2020 – today
- 2024
[j15]Sara Dubbioso
, Azarakhsh Jalalvand, Josiah Wai, Gianmaria De Tommasi, Egemen Kolemen:
Model-free stabilization via Extremum Seeking using a cost neural estimator. Expert Syst. Appl. 258: 125204 (2024)- [j14]Jaemin Seo, SangKyeun Kim, Azarakhsh Jalalvand, Rory Conlin, Andrew Rothstein, Joseph Abbate, Keith Erickson, Josiah Wai, Ricardo Shousha, Egemen Kolemen:
Avoiding fusion plasma tearing instability with deep reinforcement learning. Nat. 626(8000): 746-751 (2024) - [i4]Azarakhsh Jalalvand, Max Curie, SangKyeun Kim, Peter Steiner, Jaemin Seo, Qiming Hu, Andrew Oakleigh Nelson, Egemen Kolemen:
Diag2Diag: Multimodal super-resolution diagnostics for physics discovery with application to fusion. CoRR abs/2405.05908 (2024) - 2023
- [j13]Davi Alberto Sala, Andy Van Yperen-De Deyne, Erik Mannens, Azarakhsh Jalalvand:
Hybrid static-sensory data modeling for prediction tasks in basic oxygen furnace process. Appl. Intell. 53(12): 15163-15173 (2023) - [j12]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Exploring unsupervised pre-training for echo state networks. Neural Comput. Appl. 35(34): 24225-24242 (2023) - [j11]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Cluster-Based Input Weight Initialization for Echo State Networks. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7648-7659 (2023) - [c20]Alvin V. Garcia, Azarakhsh Jalalvand, Peter Steiner, Andrew Rothstein, Michael Van Zeeland, William W. Heidbrink, Egemen Kolemen:
Alfvén eigenmode detection using Long-Short Term Memory Networks and CO2 Interferometer data on the DIII-D National Fusion Facility. IJCNN 2023: 1-8 - [c19]Azarakhsh Jalalvand, Ors Asztalos, Mate Karacsonyi, Gergo I. Pokol:
Application of neural networks in beam emission spectroscopy modelling. IJCNN 2023: 1-8 - [c18]Jaemin Seo, Rory Conlin, Andrew Rothstein, SangKyeun Kim, Joseph Abbate, Azarakhsh Jalalvand, Egemen Kolemen:
Multimodal Prediction of Tearing Instabilities in a Tokamak. IJCNN 2023: 1-8 - [c17]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Non-Standard Echo State Networks for Video Door State Monitoring. IJCNN 2023: 1-8 - 2022
- [j10]Peter Steiner, Azarakhsh Jalalvand, Simon Stone, Peter Birkholz:
PyRCN: A toolbox for exploration and application of Reservoir Computing Networks. Eng. Appl. Artif. Intell. 113: 104964 (2022) - [j9]Azarakhsh Jalalvand, Joseph Abbate, Rory Conlin, Geert Verdoolaege, Egemen Kolemen:
Real-Time and Adaptive Reservoir Computing With Application to Profile Prediction in Fusion Plasma. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2630-2641 (2022) - 2021
- [j8]Utku Ozbulak, Baptist Vandersmissen, Azarakhsh Jalalvand, Ivo Couckuyt, Arnout Van Messem, Wesley De Neve:
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems. Comput. Vis. Image Underst. 202: 103111 (2021) - [c16]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Unsupervised Pretraining of Echo State Networks for Onset Detection. ICANN (5) 2021: 59-70 - [c15]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Improved Acoustic Modeling for Automatic Piano Music Transcription Using Echo State Networks. IWANN (2) 2021: 143-154 - [i3]Utku Ozbulak, Baptist Vandersmissen, Azarakhsh Jalalvand, Ivo Couckuyt, Arnout Van Messem, Wesley De Neve:
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems. CoRR abs/2101.10562 (2021) - [i2]Peter Steiner, Azarakhsh Jalalvand, Peter Birkholz:
Cluster-based Input Weight Initialization for Echo State Networks. CoRR abs/2103.04710 (2021) - [i1]Peter Steiner, Azarakhsh Jalalvand, Simon Stone, Peter Birkholz:
PyRCN: Exploration and Application of ESNs. CoRR abs/2103.04807 (2021) - 2020
- [j7]Baptist Vandersmissen, Nicolas Knudde, Azarakhsh Jalalvand, Ivo Couckuyt, Tom Dhaene, Wesley De Neve:
Indoor human activity recognition using high-dimensional sensors and deep neural networks. Neural Comput. Appl. 32(16): 12295-12309 (2020) - [c14]Peter Steiner, Simon Stone, Peter Birkholz, Azarakhsh Jalalvand:
Multipitch tracking in music signals using Echo State Networks. EUSIPCO 2020: 126-130 - [c13]Peter Steiner, Azarakhsh Jalalvand, Simon Stone, Peter Birkholz:
Feature Engineering and Stacked Echo State Networks for Musical Onset Detection. ICPR 2020: 9537-9544
2010 – 2019
- 2018
- [j6]Azarakhsh Jalalvand, Kris Demuynck, Wesley De Neve, Jean-Pierre Martens:
On the application of reservoir computing networks for noisy image recognition. Neurocomputing 277: 237-248 (2018) - [j5]Baptist Vandersmissen, Nicolas Knudde, Azarakhsh Jalalvand, Ivo Couckuyt, André Bourdoux, Wesley De Neve, Tom Dhaene:
Indoor Person Identification Using a Low-Power FMCW Radar. IEEE Trans. Geosci. Remote. Sens. 56(7): 3941-3952 (2018) - [c12]Davi Alberto Sala, Azarakhsh Jalalvand, Andy Van Yperen-De Deyne, Erik Mannens:
Multivariate Time Series for Data-Driven Endpoint Prediction in the Basic Oxygen Furnace. ICMLA 2018: 1419-1426 - 2017
- [c11]Poona Bahrebar, Azarakhsh Jalalvand, Dirk Stroobandt:
Dynamically Reconfigurable Architecture for Fault-Tolerant 2D Networks-on-Chip. ICCCN 2017: 1-7 - 2016
- [c10]Azarakhsh Jalalvand, Wesley De Neve, Rik Van de Walle, Jean-Pierre Martens:
Towards using Reservoir Computing Networks for noise-robust image recognition. IJCNN 2016: 1666-1672 - [c9]Baptist Vandersmissen, Lucas Sterckx, Thomas Demeester, Azarakhsh Jalalvand, Wesley De Neve, Rik Van de Walle:
An Automated End-To-End Pipeline for Fine-Grained Video Annotation using Deep Neural Networks. ICMR 2016: 409-412 - 2015
- [j4]Azarakhsh Jalalvand, Fabian Triefenbach, Kris Demuynck, Jean-Pierre Martens:
Robust continuous digit recognition using Reservoir Computing. Comput. Speech Lang. 30(1): 135-158 (2015) - [c8]Azarakhsh Jalalvand, Glenn Van Wallendael, Rik Van de Walle:
Real-Time Reservoir Computing Network-Based Systems for Detection Tasks on Visual Contents. CICSyN 2015: 146-151 - 2014
- [c7]Poona Bahrebar, Azarakhsh Jalalvand, Dirk Stroobandt:
Adaptive multicast routing method for 3D mesh-based Networks-on-Chip. SoCC 2014: 70-75 - 2013
- [j3]Fabian Triefenbach, Azarakhsh Jalalvand, Kris Demuynck, Jean-Pierre Martens:
Acoustic Modeling With Hierarchical Reservoirs. IEEE Trans. Speech Audio Process. 21(11): 2439-2450 (2013) - [c6]Fabian Triefenbach, Azarakhsh Jalalvand, Kris Demuynck, Jean-Pierre Martens:
Context-dependent modeling and speaker normalization applied to reservoir-based phone recognition. INTERSPEECH 2013: 3342-3346 - [c5]Azarakhsh Jalalvand, Kris Demuynck, Jean-Pierre Martens:
Noise robust continuous digit recognition with reservoir-based acoustic models. ISPACS 2013: 204-209 - [c4]Azarakhsh Jalalvand, Kris Demuynck, Jean-Pierre Martens:
Feature enhancement with a Reservoir-based Denoising Auto Encoder. ISSPIT 2013: 227-232 - 2012
- [c3]Azarakhsh Jalalvand, Fabian Triefenbach, Jean-Pierre Martens:
Continuous Digit Recognition in Noise: Reservoirs can do an excellent job! INTERSPEECH 2012: 1804-1807 - 2011
- [j2]Behzad Zamani, Ahmad Akbari, Babak Nasersharif, Azarakhsh Jalalvand:
Optimized discriminative transformations for speech features based on minimum classification error. Pattern Recognit. Lett. 32(7): 948-955 (2011) - [c2]Azarakhsh Jalalvand, Fabian Triefenbach, David Verstraeten, Jean-Pierre Martens:
Connected Digit Recognition by Means of Reservoir Computing. INTERSPEECH 2011: 1725-1728 - 2010
- [j1]Behzad Zamani, Ahmad Akbari, Babak Nasersharif, Mehdi Mohammadi, Azarakhsh Jalalvand:
Discriminative transformation for speech features based on genetic algorithm and HMM likelihoods. IEICE Electron. Express 7(4): 247-253 (2010) - [c1]Fabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen, Jean-Pierre Martens:
Phoneme Recognition with Large Hierarchical Reservoirs. NIPS 2010: 2307-2315
Coauthor Index
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