A systematic approach for thermal stability predictions of chemicals and their risk assessment: Pattern recognition and compounds classification based on thermal decomposition curves

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Publications associées (31)

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Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

AMER CHEMICAL SOC2023

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Current thermal comfort models used in practice do not consider physiological and psychological differences of people. With this respect, human thermo-physiology models (HTPM) are useful tools to assess human thermal comfort at local and overall levels of ...

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De novo design of protein interactions with learned surface fingerprints

Henning Paul-Julius Stahlberg, Didier Trono, Priscilla Turelli, Charlène Mireille Raymonde Raclot, Sandrine Madeleine Suzanne Georgeon, Beat Fierz, Aaron Simone Petruzzella, Anthony Marchand, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Stéphane Rosset, Alexandra Krina Van Hall-Beauvais, Alexandra Teslenko, Jane Marsden, Michael Bronstein, Casper Alexander Goverde, Stephen Michael Buckley, Dongchun Ni, Martin Pacesa

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

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Fairness and Explainability in Clustering Problems

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In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

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DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

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The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpa ...

NATURE PORTFOLIO2023

Improved extended-range prediction of persistent stratospheric perturbations using machine learning

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On average every 2 years, the stratospheric polar vortex exhibits extreme perturbations known as sudden stratospheric warmings (SSWs). The impact of these events is not limited to the stratosphere: but they can also influence the weather at the surface of ...

Copernicus Gesellschaft Mbh2023

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

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Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

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Distributional Regression and Autoregression via Optimal Transport

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We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

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Bayes-optimal Learning of Deep Random Networks of Extensive-width

Hugo Chao Cui, Florent Gérard Krzakala, Lenka Zdeborová

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Amos Sironi, Jiancheng Yang, Jian Zhou, Siqi Liu, Xiang Li, Jie Zhou

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

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