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Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Vassily Hatzimanikatis, Jasmin Maria Hafner, Anastasia Sveshnikova, Victor Luc Etienne Viterbo

Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark ...

Nature Portfolio2022

A Canvas for the Ethical Design of Learning Experiences with Digital Tools

Denis Gillet, Patrick Jermann, Roland John Tormey, Cécile Hardebolle, Adrian Christian Holzer, Jessica Elke Dehler Zufferey, Pascal Felber

The use of digital tools has drastically increased in engineering education, accelerated by the COVID-19 pandemic. These tools generate important ethical issues, in particular in terms of privacy and fairness. However, very few teacher training programmes ...

2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Rachid Guerraoui, John Stephan, Sadegh Farhadkhani, Nirupam Gupta, Rafaël Benjamin Pinot

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

PMLR2022

Game-theoretic Mechanisms for Eliciting Accurate Information

Boi Faltings

Artificial Intelligence often relies on information obtained from others through crowdsourcing, federated learning, or data markets. It is crucial to ensure that this data is accurate. Over the past 20 years, a variety of incentive mechanisms have been dev ...

2022

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Le Nguyen Hoang

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022

TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1

Michael Lehning

This study describes and evaluates a new downscaling scheme that specifically addresses the need for hillslope-scale atmospheric-forcing time series for modelling the local impact of regional climate change projections on the land surface in complex terrai ...

2022

Quantum conformance test

Elena Losero, Marco Genovese

We introduce a protocol addressing the conformance test problem, which consists in determining whether a process under test conforms to a reference one. We consider a process to be characterized by the set of end products it produces, which is generated ac ...

AMER ASSOC ADVANCEMENT SCIENCE2021

Reply to the Comment on "Phase transitions, screening and dielectric response of CsPbBr3" by S. Svirskas, S. Balciunas, M. Simenas, G. Usevicius, M. Kinka, M. Velicka, D. Kubicki, M. E. Castillo, A. Karabanov, V. V. Shvartsman, M. R. Soares, V. Sablinskas, A. N. Salak, D. C. Lupascu and J. Banys, J. Mater. Chem. A, 2020, 8, 14015

Dominik Józef Kubicki

In this reply, we address the concerns that were raised about our paper on CsPbBr3 single crystals. M. Szafranski criticized the dielectric and DSC data in our original paper claiming that they were affected by the experimental artefacts or poor quality of ...

Royal Society of Chemistry2021

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Sabine Süsstrunk, Majed El Helou, Deblina Bhattacharjee, Xiaoyu Lin

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

IEEE Institute of Electrical and Electronics Engineers2021

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

Rachid Guerraoui, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

We present GARFIELD, a library to transparently make machine learning (ML) applications, initially built with popular (but fragile) frameworks, e.g., TensorFlow and PyTorch, Byzantine–resilient. GARFIELD relies on a novel object–oriented design, reducing t ...

IEEE2021

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Reply to the Comment on "Phase transitions, screening and dielectric response of CsPbBr3" by S. Svirskas, S. Balciunas, M. Simenas, G. Usevicius, M. Kinka, M. Velicka, D. Kubicki, M. E. Castillo, A. Karabanov, V. V. Shvartsman, M. R. Soares, V. Sablinskas, A. N. Salak, D. C. Lupascu and J. Banys, J. Mater. Chem. A, 2020, 8, 14015

Dominik Józef Kubicki

Royal Society of Chemistry2021