Publications associées à Explainable ensemble learning model for predicting steel section-concrete bond strength

Publications associées (24)

Automatic identification of atmospheric bioaerosol using real-time imaging and fluorescence

Since the 1960s, the prevalence of pollen allergy has increased worldwide in developed countries and this trend is continuing, exacerbated by climate change. In the 20th century, operational pollen monitoring networks have been set-up to respond to the nee ...

EPFL2025

FADE: Forecasting for anomaly detection on ECG

David Atienza Alonso, Denisa-Andreea Constantinescu

Background and Objective: Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning and deep learning, multiple app ...

Elsevier BV2025

Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens

Lenka Zdeborová, Emanuele Troiani, Vittorio Erba, Luca Biggio

Current progress in artificial intelligence is centered around so-called large language models that consist of neural networks processing long sequences of high-dimensional vectors called tokens. Statistical physics provides powerful tools to study the fun ...

American Physical Society2025

From Prediction to Prescription: Machine Learning and Causal Inference for the Heterogeneous Treatment Effect

Elise Hélène Dumas

The increasing accumulation of medical data brings the hope of data-driven medical decision-making, but data's increasing complexity—as text or images in electronic health records—calls for complex models, such as machine learning. Here, we review how mach ...

Annual Reviews2025

Nonparametric network summaries

Arthur Verdeyme

This thesis is concerned with improving the interpretability of network summaries in both a theoretical and an applied framework, with an application to clinically relevant problems in neuroscience. The theoretical part of this thesis is concerned with gra ...

EPFL2025

Multi-Objective Management for Many-Core Computing Servers

Darong Huang

In recent decades, the rapid growth of cloud computing has transformed the technological landscape and profoundly impacted our daily lives, driven by the demand for secure, flexible, and cost-effective computing solutions. To meet these demands, computing ...

EPFL2025

Cross-Net: Joint In-Line Holographic Image Reconstruction and Refocusing

Haitao Zhou

Holography enables quantitative phase sensing through light wave interference, allowing interesting imaging modalities applied in computational microscopy where phase shift is used as a way to generate image contrast. Recovering both amplitude and phase di ...

Springer Science and Business Media Deutschland GmbH2025

GraphOntology Dataset

Francisco Pereira Correia Pinto, Ramtin Yazdanian

The EPFL Graph Platform is an open-source data infrastructure designed for academic institutions. It organizes educational and institutional data into a semantically interconnected knowledge graph, making it accessible through a graph-based search engine a ...

Zenodo2025

Using dimensionality reduction and causal inference to constrain precipitation and climate

Lucile Anna Ricard

Continued greenhouse gas emissions will lead to increasing global warming. Effective adaptation and mitigation policies depend on accurately estimating climate sensitivity, the Earth's surface temperature response to increasing CO2 emissions. Global Climat ...

EPFL2025

Anomaly Anything: Promptable Unseen Visual Anomaly Generation

Olga Fink, Han Sun

Visual anomaly detection (AD) presents significant challenges due to the scarcity of anomalous data samples. While numerous works have been proposed to synthesize anomalous samples, these synthetic anomalies often lack authenticity or require extensive tra ...

2025

GeoDistill: Geometry-Guided Self-Distillation for Weakly Supervised Cross-View Localization

Alexandre Massoud Alahi, Zimin Xia

Cross-view localization, the task of estimating a camera's 3-degrees-of-freedom (3-DoF) pose by aligning ground-level images with satellite images, is crucial for large-scale outdoor applications like autonomous navigation and augmented reality. Existing m ...

2025

Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression

Emine Berna Durmus, Suliana Manley, Joachim Lingner, Gioele La Manno, Martin Weigert, Irina Khven, Can Aztekin, Eftychia Kyriacou, Albert Dominguez Mantes, Anjalie Olivia Schläppi, Georgios Tsissios, Evangelia Skoufa

Identification of spot-like structures in large, noisy microscopy images is a crucial step for many life-science applications. Imaging-based spatial transcriptomics (iST), in particular, relies on the precise detection of millions of transcripts in low sig ...

Nature Publishing Group2025

Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: A multi-reader study

Meritxell Bach Cuadra

Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subsequent integration into clinical setting is rarely evaluated. In this work, we assess the applicability and utility of an AI-based model for brain aneurysm detect ...

2025

Fundamental Social Learning Scaling Law for Tracking Hidden Markov Models

Ali H. Sayed, Malek Khammassi

This paper studies the problem of interconnected agents collaborating to track a dynamic state from partially informative observations, where the dynamic state evolves according to a slowly varying finite-state Markov chain. Although the centralized versio ...

IEEE2025

Editorial: Advances in robots for learning

Daniel Carnieto Tozadore

we were captivated by the opportunities and challenges of integrating robots into education, and collectively, we shared a deep enthusiasm for their potential to revolutionize social robotics in meaningful ways. ...

2025

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks

Volkan Cevher, Fanghui Liu, Leello Tadesse Dadi

Recent studies show that a reproducing kernel Hilbert space (RKHS) is not a suitable space to model functions by neural networks as the curse of dimensionality (CoD) cannot be evaded when trying to approximate even a single ReLU neuron (Bach, 2017). In thi ...

2024

Intraday solar irradiance forecasting using public cameras

Demetri Psaltis, Mario Paolone, Christophe Moser, Luisa Lambertini, Ilker Oguz, Roy Sarkis

With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

Pergamon-Elsevier Science Ltd2024

Data-Driven Kinematic Modeling of Physical Origami Robots

Jamie Paik, Mustafa Mete, Alexander Michael Schüssler

Origami-inspired structures facilitate the design of compliant and compact robots. However, physical origami robots possess inherent material compliance and mechanical imperfections, presenting challenges in modeling and redundant actuation for accurate co ...

2024

Discovering meaningful units from text sequences

Melika Behjati

In recent years, the field of Natural Language Processing has seen significant revolution by the introduction of Transformers, a stack of multiple layers of attention and non-linearity, capable of performing almost any task and the backbone for large found ...

EPFL2024

Project-Based Learning Approach for an Engineering Course: Challenges and Learnings of Teaching Transversal Skills

Jamie Paik, Yousef Jalali, Iris Capdevila Tristan

Project-based learning (PBL), as one of the effective teaching and learning approaches in engineering education, can create opportunities for students to address problems with real-world applications, integrate and apply knowledge, and practice and develop ...

European Society for Engineering Education (SEFI)2024