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Related publications (28)

Equivariant Neural Architectures for Representing and Generating Graphs

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

EPFL2023

Reuse of Load-Bearing Timber Elements - Case Study of a Lookout Tower in Lausanne, Switzerland

Julius Natterer, Benoît Pascal Kälin, Corentin Jean Dominique Fivet, Jonas Warmuth, Edisson Xavier Estrella Arcos

The construction industry is jeopardizing Earth’s environment; current mitigation efforts do not suffice; and additional sustainable strategies are required. One such strategy consists of reusing structural building elements over multiple service lives. In ...

Curran Associates, Inc.2023

The Case for Performance Interfaces for Hardware Accelerators

George Candea, Aikaterini Argyraki, Rishabh Ramesh Iyer, Jiacheng Ma

While systems designers are increasingly turning to hardware accelerators for performance gains, realizing these gains is painstaking and error-prone. It can take several person-months to determine if a given accelerator is a good fit for a given piece of ...

2023

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Seyedbehzad Bozorgtabar, Devavrat Tomar

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Tes ...

Los Alamitos2023

Dispatch-aware Optimal Planning of Active Distribution Networks including Energy Storage Systems

Ji Hyun Yi

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 ...

EPFL2023

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

2023

A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary s ...

SPRINGER2022

Model-based Systems Engineering Papers Analysis based on Word Cloud Visualization

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

With the continuous improvement of system scale and complexity, model-based system engineering (MBSE) is of great importance in the practice of system engineering (SE). MBSE has been widely concerned in industry, especially in the field of complex equipmen ...

IEEE2022

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