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Publications associées (28)

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

Investigating the bioaccumulation potential of anionic organic compounds using a permanent rainbow trout liver cell line

Kristin Schirmer, Fabian Gerhard Peter Balk, Juliane Hollender

Permanent rainbow trout (Oncorhynchus mykiss) cell lines represent potential in vitro alternatives to experiments with fish. We here developed a method to assess the bioaccumulation potential of anionic organic compounds in fish, using the rainbow trout li ...

PERGAMON-ELSEVIER SCIENCE LTD2023

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Casper Alexander Goverde, Ilia Igashov, Arne Schneuing, Hamed Khakzad

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cell Press2023

Accurate color characterization of solar photovoltaic modules for building integration

Christophe Ballif, Antonin Faes, Jordi Escarre Palou, Alessandro Francesco Aldo Virtuani, Alejandro Borja Block

Accurate and reproducible color characterization is essential for colored building integrated photovoltaic products, both for manufacturing quality control and assessing long-term color stability. However, existing characterization techniques struggle to a ...

Pergamon-Elsevier Science Ltd2023

A modelling framework for modern heritage buildings energy simulation

Franz Graf, Giulia Marino, Giuseppe Galbiati

The latest European polices highlight the urgent need to rehabilitate the existing building stock, responsible for 40 % of the EU's total energy consumption. In this process, a key role is played by thermal simulations, assessing the effective energy perfo ...

Elsevier2023

Virtual metrology applied to milling process

Paul Arthur Adrien Pierre Dreyfus

Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...

EPFL2022

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Quality criteria for multi-domain studies in the indoor environment: Critical review towards research guidelines and recommendations

Mandana Sarey Khanie, Giorgia Chinazzo, Dolaana Khovalyg, Verena Marie Barthelmes, Matteo Favero

The perception, physiology, behavior, and performance of building occupants are influenced by multi-domain exposures: the simultaneous presence of multiple environmental stimuli, i.e., visual, thermal, acoustic, and air quality. Despite being extensive, th ...

PERGAMON-ELSEVIER SCIENCE LTD2022

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