Publications associées à Third correction of the Rhône River in Switzerland: physical and numerical modelling of the “Martigny bend” priority measure

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Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

Third correction of the Rhône River in Switzerland: physical and numerical modelling of the “Martigny bend” priority measure

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Chattez avec Graph Search

CFD-based analysis of pumped storage power plants implementing hydraulic short circuit operations

Twenty years of irrigation acclimation is driven by denser canopies and not by plasticity in twig- and needle-level hydraulics in a Pinus sylvestris forest

Inhalation of Microplastics—A Toxicological Complexity

Study of flexible operating conditions in variable-speed hydraulic turbines : advanced models and experimental validation

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Graph generative deep learning models with an application to circuit topologies

Identification of typical district configurations: A two-step global sensitivity analysis framework

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Reliable data-driven decision-making through optimal transport

Efficient Continual Finite-Sum Minimization

CFD-based analysis of pumped storage power plants implementing hydraulic short circuit operations

Study of flexible operating conditions in variable-speed hydraulic turbines : advanced models and experimental validation

Inhalation of Microplastics—A Toxicological Complexity

Twenty years of irrigation acclimation is driven by denser canopies and not by plasticity in twig- and needle-level hydraulics in a Pinus sylvestris forest

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Graph generative deep learning models with an application to circuit topologies

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Identification of typical district configurations: A two-step global sensitivity analysis framework

Reliable data-driven decision-making through optimal transport

Efficient Continual Finite-Sum Minimization