Publications related to Comparison of Three Imputation Methods for Groundwater Level Timeseries

On distributional autoregression and iterated transportation

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

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Sparse autoregressive neural networks for classical spin systems

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Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Contribution of standardized indexes to understand groundwater level fluctuations in response to meteorological conditions in cold and humid climates

Emmanuel Qays Dubois

Understanding the fluctuations in groundwater levels in response to meteorological conditions is challenging, especially given the slow transit time associated with groundwater reservoirs and the short duration of time series for groundwater levels. Nevert ...

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Nature-based solution enhances resilience to flooding and catalyzes multi-benefits in coastal cities in the Global South

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Coastal cities are facing a rise in groundwater levels induced by sea level rise, further triggering saturation excess flooding where groundwater levels reach the topographic surface or reduce the storage capacity of the soil, thus stressing the existing i ...

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Data-driven statistical optimization of a groundwater monitoring network

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We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

rrechaRge an R package for integrated groundwater recharge modelling

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Context • Groundwater major water resource throughout the world that is heterogeneously distributed and sustains diversified uses • The sustainability of groundwater usage highly dependent on the relative rates of groundwater abstraction e g via pumping) a ...

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Aggregating Spatial and Photometric Context for Photometric Stereo

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

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Directional sensitivity of cortical neurons towards TMS induced electric fields

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We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 24 ...

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Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

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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

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EPFL2023

Comparison of Three Imputation Methods for Groundwater Level Timeseries

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On distributional autoregression and iterated transportation

Sparse autoregressive neural networks for classical spin systems

Contribution of standardized indexes to understand groundwater level fluctuations in response to meteorological conditions in cold and humid climates

Nature-based solution enhances resilience to flooding and catalyzes multi-benefits in coastal cities in the Global South

Data-driven statistical optimization of a groundwater monitoring network

rrechaRge an R package for integrated groundwater recharge modelling

Aggregating Spatial and Photometric Context for Photometric Stereo

Directional sensitivity of cortical neurons towards TMS induced electric fields

Modeling Structured Data in Attention-based Models

Distributional Regression and Autoregression via Optimal Transport

On distributional autoregression and iterated transportation

Sparse autoregressive neural networks for classical spin systems

Contribution of standardized indexes to understand groundwater level fluctuations in response to meteorological conditions in cold and humid climates

Nature-based solution enhances resilience to flooding and catalyzes multi-benefits in coastal cities in the Global South

Data-driven statistical optimization of a groundwater monitoring network

rrechaRge an R package for integrated groundwater recharge modelling

Directional sensitivity of cortical neurons towards TMS induced electric fields

Aggregating Spatial and Photometric Context for Photometric Stereo

Distributional Regression and Autoregression via Optimal Transport

Modeling Structured Data in Attention-based Models