Publications associées à Unsupervised Electrofacies Clustering Based on Parameterization of Petrophysical Properties: A Dynamic Programming Approach

Publications associées (31)

Water weakening and the compressive brittle strength of carbonates: Influence of fracture toughness and static friction

Marie Estelle Solange Violay, Corentin Jean-Marie Rémi Noël, Barnaby Padraig Fryer

Water is ubiquitous within the pore space of rocks and has been shown to affect their physical and mechanical behaviour. Indeed, water can act on the rock strength via mechanical (i.e., reducing the effective stresses) or chemical effects (e.g., mineral di ...

2024

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Julian Thomas Blackwell, Tanja Christina Käser Jacober, Paola Mejia Domenzain, Vinitra Swamy

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

2024

A Spectral Ansatz for The Long-Time Homogenization of The Wave Equation

Matthias Benjamin Ruf

Consider the wave equation with heterogeneous coefficients in the homogenization regime. At large times, the wave interacts in a nontrivial way with the heterogeneities, giving rise to effective dispersive effects. The main achievement of the present wor ...

Ecole Polytechnique2024

Multiscale Porosity Microfluidics to Study Bacterial Transport in Heterogeneous Chemical Landscapes

Francesco Carrara, Jiande Zhou

Microfluidic models are proving to be powerful systems to study fundamental processes in porous media, due to their ability to replicate topologically complex environments while allowing detailed, quantitative observations at the pore scale. Yet, while por ...

Wiley2024

Transfer learning application of self-supervised learning in ARPES

Gabriel Aeppli

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

IOP Publishing Ltd2023

Influence of Low- to Medium-Kaolinite Clay on the Durability of Limestone Calcined Clay Cement (LC3) Concrete

Karen Scrivener

The kaolinite content is principally responsible for the durability performance of Limestone Calcined Clay Cement (LC3), which calls into question its global applicability. The clay supply has a significant impact on the LC3 system's reduced carbon footpri ...

MDPI2023

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

Yichen Xu, Qiang Liu

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 ...

Assoc Computing Machinery2023

A fully-coupled highly-parallelized geomechanical simulator for assessing induced seismicity

Jean-François Molinari, Brice Tanguy Alphonse Lecampion, Guillaume Anciaux, Nicolas Richart, Emil Gallyamov

Induced seismicity caused by anthropogenic modification of the subsurface effective stress state has been observed in a number of industrial applications -- from hydrocarbon extraction (e.g., Groningen [1]), drilling waste-water disposal (e.g., [2]) to the ...

2023

Appropriations and Uses of Travel Time

Ludy Juliana González Villamizar

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

ISTE Wiley2023

The effect of pore microstructure on strength and chloride ingress in blended cement based on low kaolin clay

Karen Scrivener, Diana Londoño Zuluaga

The objective of this study is to analyse the mechanical and durability properties of a high-performance mortars based on low grade kaolin clay and the effect of electrical conductivity and pore microstructure on the chloride penetration resistance. A tota ...

ELSEVIER2022

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Volkan Cevher, Alp Yurtsever, Maria-Luiza Vladarean

We propose a stochastic conditional gradient method (CGM) for minimizing convex finitesum objectives formed as a sum of smooth and non-smooth terms. Existing CGM variants for this template either suffer from slow convergence rates, or require carefully inc ...

2022

Physical characterization of fault rocks within the Opalinus Clay formation

Marie Estelle Solange Violay, Luis Felipe Orellana Espinoza, Christophe Nussbaum

Near-surface disposal of radioactive waste in shales is a promising option to safeguard the population and environment. However, natural faults intersecting these geological formations can potentially affect the long-term isolation of the repositories. Thi ...

Nature Research2022

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

Corinne Louise Jones

We present a discriminative clustering approach in which the feature representation can be learned from data and moreover leverage labeled data. Representation learning can give a similarity-based clustering method the ability to automatically adapt to an ...

2022

Deep MinCut: Learning Node Embeddings by Detecting Communities

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong

We present Deep MinCut (DMC), an unsupervised approach to learn node embeddings for graph -structured data. It derives node representations based on their membership in communities. As such, the embeddings directly provide insights into the graph structure ...

ELSEVIER SCI LTD2022

Zero-Knowledge IOPs with Linear-Time Prover and Polylogarithmic-Time Verifier

Alessandro Chiesa

Interactive oracle proofs (IOPs) are a multi-round generalization of probabilistically checkable proofs that play a fundamental role in the construction of efficient cryptographic proofs. ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Luca Pesce

A simple model to study subspace clustering is the high-dimensional k -Gaussian mixture model where the cluster means are sparse vectors. Here we provide an exact asymptotic characterization of the statistically optimal reconstruction error in this model i ...

2022

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

IEEE2022

Hydration and mixture design of calcined clay blended cements: review by the RILEM TC 282-CCL

Karen Scrivener, Franco Alberto Zunino Sommariva, Mohsen Ben Haha, François Henri Avet

The RILEM technical committee 282-CCL: Calcined Clays as Supplementary Cementitious Materials, investigates all the aspects related to calcined clays, from clay exploration and characterization to calcination process, hydration reactions and concrete prope ...

SPRINGER2022

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

Thomas Yu

Machine learning has become the state of the art for the solution of the diverse inverse problems arising from computer vision and medical imaging, e.g. denoising, super-resolution, de-blurring, reconstruction from scanner data, quantitative magnetic reson ...

EPFL2022

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Aude Billard, Bernardo Fichera

Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical description of the dynamics is often difficult, data-driven approaches are ...

Microtome Publishing2022