Publications associées à A benchmark dataset for machine learning in ecotoxicology

Tree diversity reduces variability in sapling survival under drought

Charlotte Grossiord, Xiaojuan Liu, Jingjing Liang

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantatio ...

Wiley2024

From roots to canopy: Unraveling the influence of species diversity on tree water relations under warmer and drier climates

Eugénie Isabelle Mas

The worsening of drought events with rising air temperature alters tree water relations causing severe hydraulic impairments and widespread forest mortality. Mixing tree species with contrasting hydraulic traits could reduce forest vulnerability to extreme ...

EPFL2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

Social media and deep learning reveal specific cultural preferences for biodiversity

Devis Tuia

Social media has created new opportunities to map cultural ecosystem services (CES) related to biodiversity at large scales. However, using these novel data to understand people's preferences in relation to these CES remains a challenge. To address this, w ...

2023

A landmark environmental law looks ahead

Devis Tuia

In late December 1973, the United States enacted what some would come to call “the pitbull of environmental laws.” In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, ob ...

American Association for the Advancement of Science2023

Fish Diversity in Relation to Littoral Habitats in Three Basins of Lake Kivu (East Africa)

Alfred Johny Wüest

In total, 28 of the 29 fish species reported from the Lake Kivu basin occur in the littoral zone of the lake, but information about their structure, occurrence, and the habitats affecting their distribution is largely lacking. The lake's inshore area is po ...

MDPI2023

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Devis Tuia, Benjamin Alexander Kellenberger

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...

2023

Mechanism balancing taxonomy

Simon Nessim Henein, Florent Cosandier, Hubert Pierre-Marie Benoît Schneegans

The balancing of mechanisms consists in distributing their moving masses, inertias, and elastic components in order to achieve key mechanical properties, such as the elimination of the shaking forces and moments exported onto their supporting structure or ...

2023

Evaluation of genetic demultiplexing of single-cell sequencing data from model species

Clement Helsens

Single-cell sequencing (sc-seq) provides a species agnostic tool to study cellular processes. However, these technologies are expensive and require sufficient cell quantities and biological replicates to avoid artifactual results. An option to address thes ...

LIFE SCIENCE ALLIANCE LLC2023

Different responses of mice and rats hippocampus CA1 pyramidal neurons to in vitro and in vivo-like inputs

Maurizio Ferdinando Pezzoli, Ying Shi, Armando Romani, Michele Migliore, Rosanna Migliore

The fundamental role of any neuron within a network is to transform complex spatiotemporal synaptic input patterns into individual output spikes. These spikes, in turn, act as inputs for other neurons in the network. Neurons must execute this function acro ...

2023

Chronic warming and dry soils limit carbon uptake and growth despite a longer growing season in beech and oak

Yann Vitasse, Charlotte Grossiord, Margaux Clara Lou Didion-Gency

Progressively warmer and drier climatic conditions impact tree phenology and carbon cycling with large consequences for forest carbon balance. However, it remains unclear how individual impacts of warming and drier soils differ from their combined effects ...

Oxford Univ Press Inc2023

Using continuous electrical conductivity measurements to derive major solute concentrations in karst systems

Paolo Benettin

Hydrochemical data of karst springs provide valuable insights into the internal hydrodynamical functioning of karst systems and support model structure identification. However, the collection of high-frequency time series of major solute species is limited ...

WILEY2023

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Emilio Maddalena

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

EPFL2023

Sulfurospirillum diekertiae sp. nov., a tetrachloroethene-respiring bacterium isolated from contaminated soil

Christof Holliger, Julien Maillard, Junxiong Wang

Two anaerobic, tetrachloroethene- (PCE-) respiring bacterial isolates, designated strain ACSDCE T and strain ACSTCE, were characterized using a polyphasic approach. Cells were Gram-stain-negative, motile, non-spore-forming and shared a vibrioid- to spirill ...

2023

Aiming beyond slight increases in accuracy

Daniel Probst

Owing to the diminishing returns of deep learning and the focus on model accuracy, machine learning for chemistry might become an endeavour exclusive to well-funded institutions and industry. Extending the focus to model efficiency and interpretability wil ...

NATURE PORTFOLIO2023

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Christian Leinenbach, Rafal Wróbel, Sergey Shevchik

Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate components easier. Yet, assessing part quality is inefficient, relying on costly Computed Tomography (CT) scans or time-consuming destructive tests. Also, intermittent inspection of ...

Elsevier Science Sa2023

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

EPFL2023

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Clémentine Léa Aguet

Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...

EPFL2023