Publications associées à Estimation of Soil Moisture from Airborne Hyperspectral Imagery with Support Vector Regression

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Investigation of microbial community dynamics in soil during variable hydrological forcing

Simiao Wang

Climate change is expected to alter the temporal distribution of precipitation events, leading to prolonged drought periods and an increased frequency of extreme precipitation events. Changes in precipitation pattern will directly affect soil moisture dyna ...

EPFL2024

Soil warming alters tree water use and canopy stomatal conductance in a mixed subtropical forest

Charlotte Grossiord, Christoph Bachofen

As air temperature and vapor pressure deficit (VPD) increase continuously, forests are losing more water through evapotranspiration, with large consequences for local and global hydrological cycles. In regions with high vegetation cover, soil warming can b ...

Elsevier2024

Spatiotemporal Dynamics of Flow and Hydrochemistry in Drainage Networks

Izabela Bujak-Ozga

Despite their high ecological value, non-perennial streams have received less attention than their perennial counterparts. This doctoral thesis addresses this disparity by advancing knowledge on the dynamics of the drainage density and hydrologic processes ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Michele Bianco, Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Tree water uptake patterns across the globe

Charlotte Grossiord, Christoph Bachofen

Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarc ...

Wiley2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Adrien Raphaël Depeursinge, Julien René Pierre Fageot, Daniel Abler

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...

Nature Portfolio2024

Efficient local linearity regularization to overcome catastrophic overfitting

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora

Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally linearly w ...

2024

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

Linking Soil Structure, Hydraulic Properties, and Organic Carbon Dynamics: A Holistic Framework to Study the Impact of Climate Change and Land Management

Sara Bonetti

Climate change and unsustainable land management practices have resulted in extensive soil degradation, including alteration of soil structure (i.e., aggregate and pore size distributions), loss of soil organic carbon, and reduction of water and nutrient h ...

2023

Global Mapping of Potential and Climatic Plant‐Available Soil Water

Dani Or, Sara Bonetti

The estimation of plant-available soil water (PASW) is essential to quantify transpiration fluxes, the onset of heatwaves, irrigation water management, land-use decisions, vegetation ecology, and land surface memory in climate models. PASW is the amount of ...

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

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

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 ...

EPFL2023

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 ...

2023

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Influence of a lossy ground on the lightning performance of overhead transmission lines

Farhad Rachidi-Haeri, Rafael Silva Alipio

This paper investigates the impact of incorporating both displacement currents and frequency-dependent soil parameters in the calculation of the ground-return impedance for the determination of the backflashover rate of 138 kV and 230 kV overhead transmiss ...

Elsevier2023

Consider the Anoxic Microsite: Acknowledging and Appreciating Spatiotemporal Redox Heterogeneity in Soils and Sediments

Vincent Noel, Meret Aeppli

Reduction-oxidation (redox) reactions underlie essentially all biogeochemical cycles. Like most soil properties and processes, redox is spatiotemporally heterogeneous. However, unlike other soil features, redox heterogeneity has yet to be incorporated into ...

AMER CHEMICAL SOC2023