Publications associées à Engineering of stable and functional metalloproteins using evolutionary computation, deep learning and simulation

Publications associées (13)

Behaviorally Relevant Information Content in Interneuron Activity

The nematode Caenorhabditis elegans offers a uniquely tractable model for studying the relationships between neuronal activity, connectivity, and behavior. Despite its simplicity, key questions remain about how information flows through its nervous system ...

EPFL2025

Stop Wasting your Cache! Bringing Machine Learning into Cache Computing

Michele Caon

The rapid evolution of Machine Learning (ML) workloads, particularly Deep Neural Networks (DNNs) and Transformer-based models, has intensified demands on computing architectures, highlighting the limitations of traditional von Neumann systems due to the me ...

ACM2025

Global Group Fairness in Federated Learning via Function Tracking

Daniel Kuhn, Yves Rychener, Yifan Hu

We investigate group fairness regularizers in federated learning, aiming to train a globally fair model in a distributed setting. Ensuring global fairness in distributed training presents unique challenges, as fairness regularizers typically involve probab ...

2025

In Situ Recrystallization and Phase Transformations in Laser Processing of Metals and Alloys : Microstructure Design and Monitoring

Claire Navarre

Laser Powder Bed Fusion (LPBF) is a method of Additive Manufacturing extensively used for metal 3D printing. It utilises a laser to selectively melt metallic powder particles based on a Computer Aided Design (CAD) model. This technique enables the construc ...

EPFL2025

Speech Data Selection for Efficient ASR Fine-Tuning using Domain Classifier and Pseudo-Label Filtering

Juan Pablo Zuluaga Gomez

In real-world speech data processing, the scarcity of annotated data and the abundance of unlabelled speech data present a significant challenge. To address this, we propose an efficient data selection pipeline for fine-tuning ASR models by generating pseu ...

Institute of Electrical and Electronics Engineers Inc.2025

Enhancing the Functionality of Layered Hybrid Perovskites

Ghewa Alsabeh

Halide perovskites have demonstrated remarkable efficiency in photovoltaics. However, their application is restricted by their limited operational stability. To address this, layered hybrid perovskites (LHPs) provided a more stable alternative. They incorp ...

EPFL2025

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

Colin Neil Jones, Yuning Jiang

This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexi ...

IEEE COMPUTER SOC2025

Gaussian universality of perceptrons with random labels

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Ludovic Théo Stephan, Federica Gerace

While classical in many theoretical settings-and in particular in statistical physics-inspired works-the assumption of Gaussian i.i.d. input data is often perceived as a strong limitation in the context of statistics and machine learning. In this study, we ...

Amer Physical Soc2024

Brief Announcement: A Case for Byzantine Machine Learning

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Sadegh Farhadkhani

The success of machine learning (ML) has been intimately linked with the availability of large amounts of data, typically collected from heterogeneous sources and processed on vast networks of computing devices (also called workers). Beyond accuracy, the u ...

ACM2024

Nissl_5, Raw images for Machine learning for histological annotation and quantification of cortical layers

Julie Meystre

This dataset contains images (TIFF image data) of brain juvenile rats Wistar Han (P14) scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F5 ...

Zenodo2024

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents

Lenka Zdeborová, Florent Gérard Krzakala, Yatin Dandi, Emanuele Troiani, Luca Pesce, Luca Arnaboldi

We investigate the training dynamics of two-layer neural networks when learning multi-index target functions. We focus on multi-pass gradient descent (GD) that reuses the batches multiple times and show that it significantly changes the conclusion about wh ...

JMLR2024

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis

Olga Fink, Florent Evariste Forest

Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an effective and flexible solution, attracting extensive research. Deep neural networks can learn rich representations from vast amounts of representative labeled data for various ap ...

2023