1.4k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR37 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR17 papers
- Université Toulouse III - Paul SabatierFR16 papers
- Université de ToulouseFR13 papers
- University of TehranIR8 papers
- Institut de Recherche en Informatique de ToulouseFR7 papers
- Brown UniversityUS5 papers
- InsermFR4 papers
- Institut de la VisionFR4 papers
- Allen Institute for Brain ScienceUS3 papers
- Image and Pervasive Access LaboratorySG3 papers
- Institute for Infocomm ResearchSG3 papers
7 papers · 1 filter
Binary Spiking Neural Networks as Causal Models
Aditya Kar, Emiliano Lorini, Timothée Masquelier
We provide a causal analysis of Binary Spiking Neural Networks (BSNNs) to explain their behavior. We formally define a BSNN and represent its spiking activity as a binary causal mo…
An Attention Mechanism for Robust Multimodal Integration in a Global Workspace Architecture
Roland Bertin-Johannet, Lara Scipio, Leopold Maytié +1
Robust multimodal systems must remain effective when some modalities are noisy, degraded, or unreliable. Existing multimodal fusion methods often learn modality selection jointly w…
AI Consciousness and Existential Risk
Rufin VanRullen
In AI, the existential risk denotes the hypothetical threat posed by an artificial system that would possess both the capability and the objective, either directly or indirectly, t…
Multimodal Dreaming: A Global Workspace Approach to World Model-Based Reinforcement Learning
Léopold Maytié, Roland Bertin Johannet, Rufin VanRullen
Humans leverage rich internal models of the world to reason about the future, imagine counterfactuals, and adapt flexibly to new situations. In Reinforcement Learning (RL), world m…
Zero-shot cross-modal transfer of Reinforcement Learning policies through a Global Workspace
Léopold Maytié, Benjamin Devillers, Alexandre Arnold +1
Humans perceive the world through multiple senses, enabling them to create a comprehensive representation of their surroundings and to generalize information across domains. For in…
Semi-supervised Multimodal Representation Learning through a Global Workspace
Benjamin Devillers, Léopold Maytié, Rufin VanRullen
Recent deep learning models can efficiently combine inputs from different modalities (e.g., images and text) and learn to align their latent representations, or to translate signal…
Deep Learning and the Global Workspace Theory
Rufin VanRullen, Ryota Kanai
Recent advances in deep learning have allowed Artificial Intelligence (AI) to reach near human-level performance in many sensory, perceptual, linguistic or cognitive tasks. There i…