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Publications associées (23)
Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks
Wenlong Liao, Qi Liu, Zhe Yang
Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online inference time consumption. To improve the quality of the solution and r ...
State Grid Electric Power Research Inst2024Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition
We study the statistical mechanics and the equilibrium dynamics of a system of classical Heisenberg spins with frustrated interactions on a d -dimensional simple hypercubic lattice, in the limit of infinite dimensionality d -> infinity . In the analysis we ...
Amer Physical Soc2024Learned Compressive Representations for Single-Photon 3D Imaging
Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Mohit Gupta
Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...
Ieee Computer Soc2023Dispatch-aware Optimal Planning of Active Distribution Networks including Energy Storage Systems
The thesis develops a planning framework for ADNs to achieve their dispatchability by means of ESS allocation while ensuring a reliable and secure operation of ADNs. Second, the framework is extended to include grid reinforcements and ESSs planning. Finall ...
EPFL2023A mathematical theory for mass lumping and its generalization with applications to isogeometric analysis
Annalisa Buffa, Espen Sande, Yannis Dirk Voet
Explicit time integration schemes coupled with Galerkin discretizations of time-dependent partial differential equations require solving a linear system with the mass matrix at each time step. For applications in structural dynamics, the solution of the li ...
2022Online Distributed Learning Over Graphs With Multitask Graph-Filter Models
In this article, we are interested in adaptive and distributed estimation of graph filters from streaming data. We formulate this problem as a consensus estimation problem over graphs, which can be addressed with diffusion LMS strategies. Most popular grap ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020A Preconditioned Graph Diffusion LMS for Adaptive Graph Signal Processing
Graph filters, defined as polynomial functions of a graph-shift operator (GSO), play a key role in signal processing over graphs. In this work, we are interested in the adaptive and distributed estimation of graph filter coefficients from streaming graph s ...
IEEE COMPUTER SOC2018