Publications related to Variational Monte Carlo Calculations of A <= 4 Nuclei with an Artificial Neural-Network Correlator Ansatz

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

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

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

Edoardo Charbon, Claudio Bruschini, Emanuele Ripiccini, Andrada Alexandra Muntean

Smarty is a fully-reconfigurable on-chip feed-forward artificial neural network (ANN) with ten integrated time-to-digital converters (TDCs) designed in a 16 nm FinFET CMOS technology node. The integration of TDCs together with an ANN aims to reduce system ...

Piscataway2024

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Fabio Nobile, Thomas Simon Spencer Trigo Trindade

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

2024

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Jean-Philippe Thiran, Tobias Kober, Bénédicte Marie Maréchal, Jonas Richiardi

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have ...

Wiley2024

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

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Richard Lee Davis, Engin Walter Bumbacher, Jérôme Guillaume Brender

How to measure students' Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types ( ...

Association for Computing Machinery2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

The complexity of quantum support vector machines

Gian Florin Gentinetta, Stefan Woerner

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

Wien2024

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Fabio Zoccolan, Gianluigi Rozza

In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing with Advection-Diffusion PDEs for high values of the Peclet number. In this situation, computational instabilities occur, both for steady and unsteady cases. A Str ...

Walter De Gruyter Gmbh2024

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Aude Billard, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Sage Publications Ltd2024

Variational Monte Carlo Calculations of A <= 4 Nuclei with an Artificial Neural-Network Correlator Ansatz

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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

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Efficient Continual Finite-Sum Minimization

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

The complexity of quantum support vector machines

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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

Efficient Continual Finite-Sum Minimization

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

The complexity of quantum support vector machines

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC