Stable blow up dynamics for energy supercritical wave equations

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Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Loris Di Natale

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

EPFL2024

Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami, Elias Per Joachim Le Boudec, Nicolas Mora Parra

Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

2024

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Fernando Porté Agel, Mohammad Jamshidmofid, Ahmad Arabkoohsar

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

Elsevier Sci Ltd2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Electrical and Optical Manifestations of Flat Band Physics in Van der Waals Materials

Gabriele Pasquale

The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...

EPFL2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Stochastic pairwise preference convergence in Bayesian agents

Max-Olivier Hongler

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

2024

Co-Design Optimisation of Morphing Topology and Control of Winged Drones

Dario Floreano, Valentin Wüest, Fabio Bergonti

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, m ...

IEEE2024

On Multiphysical Couplings in Energy Geotechnics: Relevance and Applications

Alessio Ferrari

Energy Geotechnics includes several applications related to the recovery and storage of energy from and into the ground, energy transportation, and the management of waste and carbon dioxide generated from energy use. These applications often involve the n ...

Wei Wu, Universität für Bodenkultur2023

Leveraging industrial biorefineries for the energy transition

François Maréchal, Julia Granacher

Biorefineries hold the potential to provide products and energy carriers at reduced environmental impact compared to their fossil-based counterparts. Thus, they can contribute to the decarbonization of sectors in which electrification of demands is challen ...

Elsevier Sci Ltd2023

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