B. Schrauwen

发表

The student-t mixture as a natural image patch prior with application to image compression

Benjamin Schrauwen, Aäron van den Oord, B. Schrauwen, 2014, J. Mach. Learn. Res..

Locomotion Without a Brain: Physical Reservoir Computing in Tensegrity Structures

Benjamin Schrauwen, David Verstraeten, Michiel D'Haene, 2013, Artificial Life.

Benjamin Schrauwen, Sander Dieleman, S. Dieleman, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons

Benjamin Schrauwen, Robert A. Legenstein, Lars Buesing, 2010, Neural Computation.

An overview of reservoir computing: theory, applications and implementations

Benjamin Schrauwen, Jan M. Van Campenhout, David Verstraeten, 2007, ESANN.

Band-pass Reservoir Computing

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Recurrent Kernel Machines: Computing with Infinite Echo State Networks

Benjamin Schrauwen, Michiel Hermans, B. Schrauwen, 2012, Neural Computation.

A hierarchy of recurrent networks for speech recognition

Benjamin Schrauwen, Lars Buesing, Lars Buesing, 2009, NIPS 2009.

Deep content-based music recommendation

Benjamin Schrauwen, Sander Dieleman, Aäron van den Oord, 2013, NIPS.

Memory in linear recurrent neural networks in continuous time

Benjamin Schrauwen, Michiel Hermans, B. Schrauwen, 2010, Neural Networks.

Design and control of compliant tensegrity robots through simulation and hardware validation

Benjamin Schrauwen, Andrew P. Sabelhaus, Vytas SunSpiral, 2014, Journal of The Royal Society Interface.

Oncilla Robot: A Versatile Open-Source Quadruped Research Robot With Compliant Pantograph Legs

Jochen J. Steil, Auke Jan Ijspeert, Arne Nordmann, 2018, Front. Robot. AI.

Feedback Control by Online Learning an Inverse Model

Benjamin Schrauwen, Francis Wyffels, Tim Waegeman, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Cascadable excitability in microrings.

B. Schrauwen, R. Kumar, P. Bienstman, 2012, Optics express.

Towards Learning Inverse Kinematics with a Neural Network Based Tracking Controller

Benjamin Schrauwen, Tim Waegeman, B. Schrauwen, 2011, ICONIP.

Compact hardware for real-time speech recognition using a Liquid State Machine

Benjamin Schrauwen, Jan M. Van Campenhout, David Verstraeten, 2007, 2007 International Joint Conference on Neural Networks.

Learning Slow Features with Reservoir Networks for Biologically-inspired Robot Localization

Eric A. Antonelo, B. Schrauwen, 2010 .

Reservoir Computing and Slow Feature Analysis for Autonomous Map Learning and Self-localization of Small Mobile Robots

Eric A. Antonelo, B. Schrauwen, D. Stroobandt, 2008 .

True Zero-Training Brain-Computer Interfacing – An Online Study

Klaus-Robert Müller, Benjamin Schrauwen, Michael Tangermann, 2014, PloS one.

Self-pulsation and excitability mechanism in silicon-on-insulator microrings

B. Schrauwen, P. Bienstman, J. Dambre, 2012, 2012 Asia Communications and Photonics Conference (ACP).

CAPHE: a circuit-level time-domain and frequency-domain modeling tool for nonlinear optical components

Benjamin Schrauwen, Pieter Dumon, Joni Dambre, 2011 .

UGent AMARSi progress

Francis wyffels, Benjamin Schrauwen, Jonas Degrave, 2013 .

Characterization of cascadable excitability in a silicon-on-insulator microring

Geert Morthier, Benjamin Schrauwen, Rajesh Kumar, 2012 .

Photonic reservoir computing as a new paradigm for optical information processing

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2010 .

Automatic detection of epileptic seizures on the intra-cranial electroencephalogram of rats using reservoir computing

Hans Hallez, Benjamin Schrauwen, Dirk Stroobandt, 2011, Artif. Intell. Medicine.

Optoelectronic Reservoir Computing

Benjamin Schrauwen, Yvan Paquot, Joni Dambre, 2011, Scientific Reports.

Information processing using a single dynamical node as complex system

L. Appeltant, G. Van der Sande, J. Danckaert, 2011, Nature communications.

An experimental unification of reservoir computing methods

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2007, Neural Networks.

Biologically inspired features in spiking neural networks

Benjamin Schrauwen, Dirk Stroobandt, Michiel D'Haene, 2008 .

Time-domain and frequency-domain modeling of nonlinear optical components at the circuit-level using a node-based approach

Benjamin Schrauwen, Dries Vande Ginste, Joni Dambre, 2012 .

Experimental demonstration of reservoir computing on a silicon photonics chip

Geert Morthier, Benjamin Schrauwen, David Verstraeten, 2014, Nature Communications.

Optimized Parameter Search for Large Datasets of the Regularization Parameter and Feature Selection for Ridge Regression

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2013, Neural Processing Letters.

Pruning and regularization in reservoir computing

Hendrik Van Brussel, Benjamin Schrauwen, Jan M. Van Campenhout, 2009, Neurocomputing.

Stable Output Feedback in Reservoir Computing Using Ridge Regression

Benjamin Schrauwen, Dirk Stroobandt, Francis Wyffels, 2008, ICANN.

Toward optical signal processing using photonic reservoir computing.

Benjamin Schrauwen, David Verstraeten, Roel Baets, 2008, Optics express.

Reservoir Computing Trends

Benjamin Schrauwen, Herbert Jaeger, Mantas Lukosevicius, 2012, KI - Künstliche Intelligenz.

Terrain Classification for a Quadruped Robot

Benjamin Schrauwen, Jonas Degrave, Francis Wyffels, 2013, 2013 12th International Conference on Machine Learning and Applications.

Distance dependent extensions of the Chinese restaurant process

Willem A. M. Wybo, Pieter-Jan Kindermans, B. Schrauwen, 2012 .

Learning slow features with reservoir computing for biologically-inspired robot localization

Benjamin Schrauwen, Eric A. Antonelo, B. Schrauwen, 2012, Neural Networks.

Accelerating Event-Driven Simulation of Spiking Neurons with Multiple Synaptic Time Constants

Benjamin Schrauwen, Jan M. Van Campenhout, Dirk Stroobandt, 2009, Neural Computation.

Time series classification for the prediction of dialysis in critically ill patients using echo statenetworks

Filip De Turck, Tom Dhaene, Benjamin Schrauwen, 2013, Eng. Appl. Artif. Intell..

Parallel Reservoir Computing Using Optical Amplifiers

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2011, IEEE Transactions on Neural Networks.

Improving reservoirs using intrinsic plasticity

Jochen J. Steil, Benjamin Schrauwen, Dirk Stroobandt, 2008, Neurocomputing.

Information Processing Capacity of Dynamical Systems

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2012, Scientific Reports.

Automated Design of Complex Dynamic Systems

Benjamin Schrauwen, Joni Dambre, Peter Bienstman, 2014, PloS one.

Frequency modulation of large oscillatory neural networks

Benjamin Schrauwen, Herbert Jaeger, Francis Wyffels, 2014, Biological Cybernetics.

Towards a Neural Hierarchy of Time Scales for Motor Control

Benjamin Schrauwen, Francis Wyffels, Tim Waegeman, 2012, SAB.

Design of a Central Pattern Generator Using Reservoir Computing for Learning Human Motion

Benjamin Schrauwen, Francis Wyffels, B. Schrauwen, 2009, 2009 Advanced Technologies for Enhanced Quality of Life.

Sign Language Recognition Using Convolutional Neural Networks

Benjamin Schrauwen, Sander Dieleman, Lionel Pigou, 2014, ECCV Workshops.

Training and Analysing Deep Recurrent Neural Networks

Benjamin Schrauwen, Michiel Hermans, B. Schrauwen, 2013, NIPS.

Transfer Learning by Supervised Pre-training for Audio-based Music Classification

Benjamin Schrauwen, Sander Dieleman, Aäron van den Oord, 2014, ISMIR.

Real-Time Epileptic Seizure Detection on Intra-cranial Rat Data Using Reservoir Computing

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2008, ICONIP.

Extending SpikeProp

B. Schrauwen, J. Van Campenhout, J. V. Campenhout, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Defect Detection in Reinforced Concrete Using Random Neural Architectures

Benjamin Schrauwen, David Verstraeten, John B. Butcher, 2014, Comput. Aided Civ. Infrastructure Eng..

On Learning Navigation Behaviors for Small Mobile Robots With Reservoir Computing Architectures

Benjamin Schrauwen, Eric A. Antonelo, B. Schrauwen, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Isolated word recognition with the Liquid State Machine: a case study

B. Schrauwen, D. Verstraeten, D. Stroobandt, 2005, Inf. Process. Lett..

Compact hardware liquid state machines on FPGA for real-time speech recognition

Benjamin Schrauwen, Jan M. Van Campenhout, David Verstraeten, 2008, Neural Networks.

An uncued brain-computer interface using reservoir computing

Benjamin Schrauwen, David Verstraeten, Pieter-Jan Kindermans, 2010, NIPS 2010.

Training energy-based models for time-series imputation

Benjamin Schrauwen, Dirk Stroobandt, Philemon Brakel, 2013, J. Mach. Learn. Res..

Memory in reservoirs for high dimensional input

Benjamin Schrauwen, Michiel Hermans, B. Schrauwen, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Memory versus non-linearity in reservoirs

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

A comparative study of Reservoir Computing strategies for monthly time series prediction

Benjamin Schrauwen, Francis Wyffels, B. Schrauwen, 2010, Neurocomputing.

On the Quantification of Dynamics in Reservoir Computing

Benjamin Schrauwen, David Verstraeten, B. Schrauwen, 2009, ICANN.

Information Processing Capacity of

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2012 .

Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic

Benjamin Schrauwen, Jan M. Van Campenhout, J. V. Campenhout, 2006, ESANN.

Phoneme Recognition with Large Hierarchical Reservoirs

Benjamin Schrauwen, Jean-Pierre Martens, Azarakhsh Jalalvand, 2010, NIPS.

A discrete/rhythmic pattern generating RNN

Benjamin Schrauwen, Francis Wyffels, Tim Waegeman, 2012, ESANN.

On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing

Benjamin Schrauwen, Robert A. Legenstein, Lars Buesing, 2008, NIPS.

Memristor Models for Machine Learning

Benjamin Schrauwen, Michiel Hermans, Joni Dambre, 2014, Neural Computation.

Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller

Klaus-Robert Müller, Benjamin Schrauwen, Michael Tangermann, 2014, Journal of neural engineering.

Factoring Variations in Natural Images with Deep Gaussian Mixture Models

Benjamin Schrauwen, Aäron van den Oord, B. Schrauwen, 2014, NIPS.

Training and analyzing deep recurrent neural networks

Benjamin Schrauwen, Michiel Hermans, B. Schrauwen, 2013, NIPS 2013.

Realization of a passive compliant robot dog

Benjamin Schrauwen, Michiel D'Haene, Francis Wyffels, 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns

Benjamin Schrauwen, David Verstraeten, Joni Dambre, 2014, IEEE Transactions on Neural Networks and Learning Systems.

BSA, a fast and accurate spike train encoding scheme

B. Schrauwen, J. Van Campenhout, B. Schrauwen, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Oger: modular learning architectures for large-scale sequential processing

Benjamin Schrauwen, Sander Dieleman, David Verstraeten, 2012, J. Mach. Learn. Res..

The body as a reservoir: locomotion and sensing with linear feedback

Benjamin Schrauwen, Ken Caluwaerts, B. Schrauwen, 2011 .

Reservoir Computing with Stochastic Bitstream Neurons

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2005 .

The Introduction of Time-Scales in Reservoir Computing, Applied to Isolated Digits Recognition

Benjamin Schrauwen, Jan M. Van Campenhout, David Verstraeten, 2007, ICANN.

Using topic models for Twitter hashtag recommendation

Wesley De Neve, Rik Van de Walle, Benjamin Schrauwen, 2013, WWW.

Reservoir-based techniques for speech recognition

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Reservoir computing using a delayed feedback system: towards photonic implementations

Benjamin Schrauwen, Miguel C. Soriano, Lennert Appeltant, 2011 .

A Bayesian Model for Exploiting Application Constraints to Enable Unsupervised Training of a P300-based BCI

Benjamin Schrauwen, David Verstraeten, Pieter-Jan Kindermans, 2012, PloS one.

Reservoir computing and extreme learning machines for non-linear time-series data analysis

B. Schrauwen, D. Verstraeten, J. B. Butcher, 2013, Neural Networks.

Learning a piecewise linear transform coding scheme for images

Benjamin Schrauwen, Aäron van den Oord, Sander Dieleman, 2013, International Conference on Graphic and Image Processing.

Audio-based Music Classification with a Pretrained Convolutional Network

Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, 2011, ISMIR.

Multiscale Approaches To Music Audio Feature Learning

Benjamin Schrauwen, Sander Dieleman, S. Dieleman, 2013, ISMIR.

2007 Special Issue: An experimental unification of reservoir computing methods

B. Schrauwen, Michiel D'Haene, D. Verstraeten, 2007 .

Experiments with Reservoir Computing on the road sign problem

Benjamin Schrauwen, Dirk Stroobandt, Eric A. Antonelo, 2016 .

The spectral radius remains a valid indicator of the Echo state property for large reservoirs

Benjamin Schrauwen, Sander Dieleman, Francis Wyffels, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Recent advances in optical Reservoir Computing

Benjamin Schrauwen, Yvan Paquot, Joni Dambre, 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

Computing using delayed feedback systems: towards photonics

L. Appeltant, M. C. Soriano, G. Van der Sande, 2012, Photonics Europe.

Pruning reservoirs with Random Static Projections

B. Schrauwen, D. Verstraeten, J.B. Butcher, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Supervised learning of internal models for autonomous goal-oriented robot navigation using Reservoir Computing

Benjamin Schrauwen, Eric A. Antonelo, B. Schrauwen, 2010, 2010 IEEE International Conference on Robotics and Automation.

Modular reservoir computing networks for imitation learning of multiple robot behaviors

Benjamin Schrauwen, Francis Wyffels, Tim Waegeman, 2009, 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA).

Non-Markovian Processes Modeling with Echo State Networks

Hendrik Van Brussel, Benjamin Schrauwen, Xavier Dutoit, 2009, ESANN 2009.

Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing

Benjamin Schrauwen, Dirk Stroobandt, Eric A. Antonelo, 2008, 2008 10th Brazilian Symposium on Neural Networks.

Modeling multiple autonomous robot behaviors and behavior switching with a single reservoir computing network

Benjamin Schrauwen, Dirk Stroobandt, Eric A. Antonelo, 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.

Photonic Reservoir Computing with Coupled Semiconductor Optical Amplifiers

Benjamin Schrauwen, Jan M. Van Campenhout, Roel Baets, 2008, OSC.

Event detection and localization for small mobile robots using reservoir computing

Benjamin Schrauwen, Dirk Stroobandt, Eric A. Antonelo, 2008, Neural Networks.

Mobile robot control in the road sign problem using Reservoir Computing networks

Benjamin Schrauwen, Dirk Stroobandt, Eric A. Antonelo, 2008, 2008 IEEE International Conference on Robotics and Automation.

Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing

Benjamin Schrauwen, Jan M. Van Campenhout, Eric A. Antonelo, 2007, Neural Processing Letters.

Event Detection and Localization in Mobile Robot Navigation Using Reservoir Computing

Benjamin Schrauwen, Dirk Stroobandt, Marnix Nuttin, 2007, ICANN.

Technical report on Hierarchical Reservoir Computing architectures

Benjamin Schrauwen, Tim Waegeman, B. Schrauwen, 2012 .

System modeling for active noise control with reservoir computing

Benjamin Schrauwen, Tim Waegeman, Ken Caluwaerts, 2012 .

Reservoir computing using a delayed feedback system : towards photonics

M. C. Soriano, B. Schrauwen, S. Massar, 2011 .

Extending reservoir computing with random static projections: a hybrid between extreme learning and RC

Benjamin Schrauwen, Charles Day, David Verstraeten, 2010, ESANN.

Comparative evaluation of approaches in T.4.1-4.3 and working definition of adaptive module

Jochen J. Steil, Auke Jan Ijspeert, Francis wyffels, 2010 .

Non-markovian process modelling with Echo State Networks

Hendrik Van Brussel, Benjamin Schrauwen, Xavier Dutoit, 2009, ESANN.

Recent advances in efficient learning of recurrent networks

Jochen J. Steil, Barbara Hammer, Benjamin Schrauwen, 2009, ESANN.

Using reservoir computing in a decomposition approach for time series prediction

Francis wyffels, Benjamin Schrauwen, Dirk Stroobandt, 2008 .

System modeling with Reservoir Computing

Francis wyffels, Benjamin Schrauwen, Dirk Stroobandt, 2008 .

Adapting reservoirs to get Gaussian distributions

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2007 .

Accelerating Event Based Simulation for Multi-synapse Spiking Neural Networks

Benjamin Schrauwen, Dirk Stroobandt, Michiel D'Haene, 2006, ICANN.

Learning Navigation Attractors For Mobile Robots With Reinforcement Learning And Reservoir Computing

Benjamin Schrauwen, Eric A. Antonelo, Eric Aislan Antonelo, 2016 .

Real-time detection of epileptic seizures in animal models using reservoir computing

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2013, Epilepsy Research.

Analog readout for optical reservoir computers

Benjamin Schrauwen, Yvan Paquot, Serge Massar, 2012, NIPS.

Towards autonomous self-localization of small mobile robots using reservoir computing and slow feature analysis

Benjamin Schrauwen, Eric A. Antonelo, B. Schrauwen, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots

Benjamin Schrauwen, Eric A. Antonelo, B. Schrauwen, 2009, ICANN.

Pruning and Regularisation in Reservoir Computing: a First Insight

Hendrik Van Brussel, Benjamin Schrauwen, Jan M. Van Campenhout, 2008, ESANN.

Epileptic seizure detection using Reservoir Computing

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2008 .

Applying morphological changes during the evolution of quadruped robots results in robust gaits

Francis wyffels, Benjamin Schrauwen, Jonas Degrave, 2012 .

Towards incorporation of hierarchical Bayesian models into evolution strategies for quadruped gait generation

Francis wyffels, Benjamin Schrauwen, Ken Caluwaerts, 2012 .

Bat echolocation modelling using spike kernels with Support Vector Regression

Herbert Peremans, Benjamin Schrauwen, Bertrand Fontaine, 2007, ESANN.

Event management for large scale event-driven digital hardware spiking neural networks

Louis-Charles Caron, Jean Rouat, Benjamin Schrauwen, 2013, Neural Networks.

Optical information processing: Advances in nanophotonic reservoir computing

J. Dambre, B. Schrauwen, P. Bienstman, 2012, 2012 14th International Conference on Transparent Optical Networks (ICTON).

Machine Learning Techniques based on Random Projections

Amaury Lendasse, Benjamin Schrauwen, Yoan Miché, 2010, ESANN.

A Unified Probabilistic Approach to Improve Spelling in an Event-Related Potential-Based Brain–Computer Interface

Benjamin Schrauwen, Pieter-Jan Kindermans, Hannes Verschore, 2013, IEEE Transactions on Biomedical Engineering.

Experimental demonstration of reservoir computing on a silicon photonics chip

B. Schrauwen, D. Verstraeten, P. Bienstman, 2014, Nature Communications.

Isolated word recognition using a Liquid State Machine

Benjamin Schrauwen, Dirk Stroobandt, David Verstraeten, 2005, ESANN.

Improving SpikeProp: Enhancements to An Error-Backpropagation Rule for Spiking Neural Networks

Benjamin Schrauwen, Jan Van Campenhout, J. V. Campenhout, 2004 .

On implementing reservoir computing

Benjamin Schrauwen, B. Schrauwen, 2006, Neural Information Processing Systems.

Artificial Intelligence at Light Speed: towards Opto-Electronic Reservoir Computing

Benjamin Schrauwen, Yvan Paquot, Joni Dambre, 2010 .

A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling

Benjamin Schrauwen, David Verstraeten, Pieter-Jan Kindermans, 2012, NIPS.

Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization

Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, 2012, ICANN.