Publications related to Pre-bcc: A novel integrated machine learning framework for predicting mechanical and durability properties of blended cement concrete

Random matrix methods for high-dimensional machine learning models

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

Decarbonization potential of steel fibre-reinforced limestone calcined clay cement concrete one-way slabs

Hisham Tarek Mohamed Hafez

This study deals with a comparison of the environmental performance of one-way slabs utilizing steel fibrereinforced limestone calcined clay cement (LC3) concrete with the control case of Ordinary Portland cement concrete. The experimental program constitu ...

Elsevier Sci Ltd2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Additively manufactured steel reinforcement for small scale reinforced concrete modeling: Tensile and bond behavior

Christian Leinenbach, Rafal Wróbel

Small scale (1:30-1:40) Reinforced Concrete is useful for centrifuge testing. However, manufacturing the reinforcing cages by hand at this scale is practically difficult. This paper suggests that small scale reinforcement can be manufactured using a metal ...

Elsevier Sci Ltd2024

Contradict mechanism of long-term magnesium and sodium sulfate attacks of nano silica-modified cement mortars - Experimental and thermodynamic modeling

Qiao Wang

The mechanisms of external sulfate attack on cement mortars containing nano silica have been studied under full immersion conditions after 3 years. The sulfate degradation processes were compared between sodium sulfate and magnesium sulfate solutions with ...

Elsevier Sci Ltd2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

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

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

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

Contributions to rebar-to-concrete interaction and its structural implications for design and monitoring applications

Enrique Corres Sojo

Bond between reinforcing bars and concrete has been the focus of extensive research over the last century. This is well-justified as the functioning of reinforced concrete intimately depends on the interaction between rebar and concrete, as for example cra ...

EPFL2024

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

2024