| Look and Feel What and How Recurrent Self-Organizing Maps Learn. | 0 | 0.34 | 2019 |
| Reconstruction d'état caché avec cartes auto-organisatrices récurrentes. | 0 | 0.34 | 2018 |
| Towards an effective multi-map self organizing recurrent neuronal network. | 0 | 0.34 | 2014 |
| Cellular Computing and Least Squares for Partial Differential Problems Parallel Solving. | 0 | 0.34 | 2014 |
| A C++ template-based reinforcement learning library: fitting the code to the mathematics | 3 | 0.44 | 2013 |
| Tracking non-stationary dynamical system phase using multi-map and temporal self-organizing architecture. | 0 | 0.34 | 2011 |
| Dynamic neural field optimization using the unscented Kalman filter | 0 | 0.34 | 2011 |
| Sample-efficient batch reinforcement learning for dialogue management optimization | 27 | 1.11 | 2011 |
| Online speaker diarization with a size-monitored growing neural gas algorithm. | 0 | 0.34 | 2010 |
| InterCell: a software suite for rapid prototyping and parallel execution of fine grained applications | 0 | 0.34 | 2010 |
| Application-Driven Parameter Tuning Methodology for Dynamic Neural Field Equations | 1 | 0.37 | 2009 |
| Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network | 25 | 0.98 | 2008 |
| Are Neural Fields Suitable for Vector Quantization? | 2 | 0.43 | 2008 |
| Tracking fast changing non-stationary distributions with a topologically adaptive neural network: application to video tracking | 1 | 0.38 | 2007 |
| Model of multi-modal cortical processing: Coherent learning in self-organizing modules. | 7 | 0.72 | 2005 |
| Towards word semantics from multi-modal acoustico-motor integration: application of the bijama model to the setting of action-dependant phonetic representations | 1 | 0.35 | 2005 |
| Making competition in neural fields suitable for computational architectures | 3 | 0.47 | 2005 |
| From a biological to a computational model for the autonomous behavior of an animat | 5 | 0.59 | 2002 |
| Action Scheme Scheduling with a Neural Architecture: A Prefrontal Cortex Approach | 0 | 0.34 | 2002 |
| Integration of Biologically Inspired Temporal Mechanisms into a Cortical Framework fo Sequence Processing | 2 | 0.57 | 2001 |
| Specialization with cortical models: An application to causality learning | 3 | 0.75 | 1999 |
