Publications associées à Combining computational fluid dynamics and neural networks to characterize microclimate extremes: Learning the complex interactions between meso-climate and urban morphology

Publications associées (22)

Using dimensionality reduction and causal inference to constrain precipitation and climate

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

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

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

Sophie Catherine Erb

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

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

Multilevel emission impacts of electrification and coal pathways in China's net-zero transition

Yuxin Yin

Decarbonizing China's energy system requires both greening the power supply and electrifying end-use sectors. However, concerns exist that electrification may increase emissions while coal power dominates. Using a global climate model, we explore electrifi ...

2025

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

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

Pose-Invariant Face Recognition via Feature-Space Pose Frontalization

Nikolay Georgiev Stanishev, Touradj Ebrahimi, Yuhang Lu

Pose-invariant face recognition has become a challenging problem for modern AI-based face recognition systems. It aims at matching a profile face captured in the wild with a frontal face registered in a database. Existing methods perform face frontalizatio ...

IEEE2025

Modeling the Effect of Trees on Energy Demand for Indoor Cooling and Dehumidification Across Cities and Climates

Gabriele Manoli

Increasing urban tree cover is a common strategy to lower urban temperatures and indirectly the building energy demand for air-conditioning (AC). However, urban vegetation leads to increasing humidity with potential negative effects on the AC dehumidificat ...

AMER GEOPHYSICAL UNION2025

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

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

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

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

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

Towards Robust Vision Models

Harshitha Machiraju

Deep convolutional neural networks (DCNNs) have significantly advanced the field of computer vision and are often considered as plausible models for the human visual system. However, they still have several vulnerabilities in terms of adversarial attacks, ...

EPFL2024

Prompt-guided and multimodal landscape scenicness assessments with vision-language models

Devis Tuia

Recent advances in deep learning and Vision-Language Models (VLM) have enabled efficient transfer to downstream tasks even when limited labelled training data is available, as well as for text to be directly compared to image content. These properties of V ...

PUBLIC LIBRARY SCIENCE2024

Online Learning of Continuous Signed Distance Fields Using Piecewise Polynomials

Ante Maric, Yiming Li, Sylvain Calinon

Reasoning about distance is indispensable for establishing or avoiding contact in manipulation tasks. To this end, we present an online approach for learning implicit representations of signed distance using piecewise polynomial basis functions. Starting f ...

Ieee-Inst Electrical Electronics Engineers Inc2024

SuperAnimal pretrained pose estimation models for behavioral analysis

Alexander Mathis, Mackenzie Mathis, Shaokai Ye, Steffen Schneider, Jessy Lauer, Tian Qiu, Maxime Michel André Vidal, Anastasiia Filippova

Quantification of behavior is critical in diverse applications from neuroscience, veterinary medicine to animal conservation. A common key step for behavioral analysis is first extracting relevant keypoints on animals, known as pose estimation. However, re ...

Nature Research2024

Bayesian optimisation for additive screening and yield improvements - beyond one-hot encoding

Philippe Schwaller, Bojana Rankovic

Reaction additives are critical in dictating the outcomes of chemical processes making their effective screening vital for research. Conventional high-throughput experimentation tools can screen multiple reaction components rapidly. However, they are prohi ...

2024

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Guillaume Marc Georges Vray, Devavrat Tomar

Developing computational pathology models is essential for reducing manual tissue typing from whole slide images, transferring knowledge from the source domain to an unlabeled, shifted target domain, and identifying unseen categories. We propose a practica ...

Institute of Electrical and Electronics Engineers2024