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Decision system for smart management of resources in warehouses – AGIRE
Designing an efficient, reactive warehouse able to respond to demand variations is a significant challenge to address. A fully automated warehouse cannot be considered as a solution. Indeed, the investments required to satisfy appropriately demand peaks are too large to be considered. A more suitabl
Decomposition of Graphical Models – DE-MO-GRAPH
Solving NP-hard problems is still a challenge at the theoretical or practical level. This project aims at solving decision, optimization and counting (discrete integration) problems defined as "graphical models" (constraint or cost function networks, bayesian networks, propositional logic and Markov
Deep Co-design of a Privacy Preserving Intelligent Camera – DOOPLER
Today, we are surrounded by surveillance systems that generate billions of images per day processed by computer vision techniques. This situation raises legal issues related to privacy. If privacy is sometimes protected by post-processing the images, for example by blurring them, this protection ca
Deep Learning for Analysis of Electron Microscopy Imaging of Nanoalloys – Nano-Insight
Nanoalloys, owing to their unique properties, have applications in catalysis and sensing. The crux of maximizing their potential lies in the ability to design them with precise size, morphology, and chemical composition. Although several synthesis methods exist, a comprehensive characterization tech
Deep Learning for Constraint Optimization – DELCO
This project aims at building on recent progress in game playing and deep reinforcement learning to design a new generation of more general constraint satisfaction and optimization solvers. Upon completion, this project will contribute to make basic (or even naive) problem formulations far more e
Deep Learning for Prediction of Judicial Outcome – LAWBOT
LAWBOT is first, an applied research project in law, on the use of automated natural language processing techniques. The LAWBOT project aims to create an artificial case-law intelligence capable of predicting the judicial outcome for a given case, by imitating the decisions previously rendered by th
Deep Learning meets Numerical Analysis – DeepNuM
OBJECTIVE: DeepNuM aims at developing the interplay between two families of computational approaches, Deep Neural Networks (DNNs) and Partial Differential Equations (PDEs), with the goal of modeling complex dynamical systems arising from the observation of natural phenomena. Three central questions
Deep Neural Networks for the design of photonic devices – DNN4Photonics
The urgent need for innovative solutions underscores the transformative impact of enhanced modeling in advancing large-scale nanophotonics. To address these challenges and expedite the design process, recent studies have explored the potential of Artificial Intelligence (AI), specifically Deep Lear
Deep Spiking networks for Embedded and Efficient intelligence in autonomous systems – DeepSee
Autonomous and intelligent embedded solutions are mainly designed as cognitive systems composed of a three step process: perception, decision and action, periodically invoked in a closed-loop manner in order to detect changes in the environment and appropriately choose the actions to be performed ac
Deep generative and inference models for weakly-supervised speech enhancement – DEGREASE
Remote human interaction and human-machine interaction require reliable speech-processing technologies that can work in unconstrained real-world acoustic conditions. Speech recordings are inevitably contaminated by interfering sound sources and by the presence of reverberation. Whether for human or
