454 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- InsermFR6 papers
- École Normale Supérieure - PSLFR5 papers
- Université Paris Sciences et LettresFR5 papers
- Laboratoire de Neurosciences CognitivesFR4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Gatsby Computational Neuroscience UnitGB2 papers
- Laboratoire de Physique de l'Ecole Normale SupérieureFR2 papers
- University College LondonGB2 papers
- École Normale SupérieureBI1 paper
- Institut Systèmes Intelligents et de RobotiqueFR1 paper
- Laboratoire de Physique Théorique et Modèles StatistiquesFR1 paper
- Laboratoire de Statistique Théorique et AppliquéeFR1 paper
6 papers
Shaping dynamics with multiple populations in low-rank recurrent networks
Manuel Beiran, Alexis Dubreuil, Adrian Valente +2
An emerging paradigm proposes that neural computations can be understood at the level of dynamical systems that govern low-dimensional trajectories of collective neural activity. H…
Dynamics of random recurrent networks with correlated low-rank structure
Friedrich Schuessler, Alexis Dubreuil, Francesca Mastrogiuseppe +2
A given neural network in the brain is involved in many different tasks. This implies that, when considering a specific task, the network's connectivity contains a component which…
Interactively shaping robot behaviour with unlabeled human instructions
Anis Najar, Olivier Sigaud, Mohamed Chetouani
In this paper, we propose a framework that enables a human teacher to shape a robot behaviour by interactively providing it with unlabeled instructions. We ground the meaning of in…
Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks
Manuel Beiran, Srdjan Ostojic
Neural activity exhibits a vast range of timescales that can be several fold larger than the membrane time constant of individual neurons. Two types of mechanisms have been propose…
A geometrical analysis of global stability in trained feedback networks
Francesca Mastrogiuseppe, Srdjan Ostojic
Recurrent neural networks have been extensively studied in the context of neuroscience and machine learning due to their ability to implement complex computations. While substantia…
Linking connectivity, dynamics and computations in low-rank recurrent neural networks
Francesca Mastrogiuseppe, Srdjan Ostojic
Large scale neural recordings have established that the transformation of sensory stimuli into motor outputs relies on low-dimensional dynamics at the population level, while indiv…