Found 16 document(s)
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We present a new hybrid architecture that combines the advantages of Transformer and Reservoir Computing to overcome the inherent quadratic complexity of traditional Transformer. Our approach integrates working memory th...
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The brain's ability to detect behaviorally relevant stimuli from sensory inputs is fundamental to cognition, yet the neural mechanisms linking synaptic processes to event-related potential (ERP) signatures remain unclear...
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Controlling a prosthetic upper limb requires the reconstruction of multiple distal articulations. Moreover, the higher the amputation level, the more joints need to be reconstructed, and the less kinetic information is a...
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Brain encoding is the process of mapping stimuli to brain activity. There is a vast literature on linguistic brain encoding for functional MRI (fMRI) related to syntactic and semantic representations. Magnetoencephalogra...
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En février 2023, un projet de deux jours mené par Xavier Hinaut et Nathan Trouvain de l'équipe Mnemosyne de l'Inria s'est concentré sur la présentation du Reservoir Computing, de Reservoirpy (un outil Python pour le Rese...
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An interesting way to evaluate the representations obtained with machine learning language models is to compared them with human brain recordings. Encoding models have been used to partially predict fMRI recordings of di...
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Several popular sequence-based and pretrained language models have been found to be successful for text-driven prediction of brain activations. However, these models still lack longterm memory plausibility (i.e. how they...
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Syntactic parsing is the task of assigning a syntactic structure to a sentence. Recent works have used syntactic embeddings from constituency trees and other word syntactic features to understand how syntax structure is ...
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We propose a novel architecture called Hierarchical-Task Reservoir (HTR) suitable for real-time sentence parsing from continuous speech. Accordingly, we introduce a novel task that consists in performing anytime Part-of-...
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Recurrent Neural Networks Models for Developmental Language Acquisition: Reservoirs Outperform LSTMsWe previously developed cortico-striatal models for sentence comprehension (Hinaut & Dominey 2013) and sentence production (Hinaut et al. 2015). The sentence comprehension model is based on the reservoir computing princi...
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The prefrontal cortex is known to be involved in many high-level cognitive functions, in particular, working memory. Here, we study to what extent a group of randomly connected units (namely an Echo State Network, ESN) c...
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There has been an important progress these last years in speech recognition systems. The word recognition error rate went down with the arrival of deep learning methods. However, if one uses cloud speech API and integrat...
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We present a Recurrent Neural Network (RNN), namely an Echo State Network (ESN), that performs sentence comprehension and can be used for Human-Robot Interaction (HRI). The RNN is trained to map sentence structures to me...
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In this paper we present our experiments with an echo state network (ESN) for the task of classifying high-level human activities from video data. ESNs are recurrent neural networks which are biologically plausible, fast...