Publications related to Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Related publications (32)

Optimizing fairness and utility in healthcare machine learning models

Demographic fairness or equity is a crucial aspect of machine learning models, particularly in critical domains such as healthcare, where errors can have severe consequences. A fair model avoids making distinctions between groups with different sensitive o ...

2025

Theory and applications of the sum-of-squares technique

Luca Pesce, Giovanni Piccioli, Elisabetta Cornacchia

The sum-of-squares (SOS) approximation method is a technique used in optimization problems to derive lower bounds on the optimal value of an objective function. By representing the objective function as a sum of squares in a feature space, the SOS method t ...

2024

Neural Redshift: Random Networks are not Random Functions

Valentin Hartmann

Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but they cannot account for the capabilities of models from gradient-free metho ...

IEEE2024

Statistical mechanics of deep learning

Freya Behrens

2024

Socially Intelligent Networks: A framework for decision making over graphs

Ali H. Sayed

By 'social learning,' in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents' decisions evolve dynamically through interactions with neighbors and the environment. The study of social learni ...

2024

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

2024

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

Propulsion and energetics of a minimal magnetic microswimmer

Ignacio Pagonabarraga Mora

In this manuscript we describe the realization of a minimal hybrid microswimmer, composed of a ferromagnetic nanorod and a paramagnetic microsphere. The unbounded pair is propelled in water upon application of a swinging magnetic field that induces a perio ...

ROYAL SOC CHEMISTRY2020

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

Transforming scholarship in the archives through handwritten text recognition Transkribus as a case study

Frédéric Kaplan, Sofia Ares Oliveira

Purpose An overview of the current use of handwritten text recognition (HTR) on archival manuscript material, as provided by the EU H2020 funded Transkribus platform. It explains HTR, demonstrates Transkribus, gives examples of use cases, highlights the af ...

2019

The Resource Identification Initiative: A cultural shift in publishing

Sean Lewis Hill

A central tenet in support of research reproducibility is the ability to uniquely identify research resources, i.e., reagents, tools, and materials that are used to perform experiments. However, current reporting practices for research resources are insuff ...

2015

A measure for the impact of research

The last few years have seen the proliferation of measures that quantify the scientific output of researchers. Yet, most of these measures focus on productivity, thus fostering the "publish or perish" paradigm. This article proposes a measure that aims at ...

Nature Publishing Group2013

Validating functional redundancy with mixed generative adversarial networks

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Thanh Trung Huynh

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

ELSEVIER2023

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Varun Sharma, Yi Zhang, Lei Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Jessica Prisciandaro, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Guido Andreassi, Arvind Shah, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Federica Legger, Gabriele Grosso

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used i ...

American Physical Society2023

Synthesis of poly(methacrylic acid) brushes via surface-initiated atom transfer radical polymerization of sodium methacrylate and their use as substrates for the mineralization of calcium carbonate

Harm-Anton Klok, Stefano Tugulu, Raphaël Barbey

This manuscript describes the synthesis of poly(methacrylic acid) (PMAA) brushes via surface-initiated atom transfer radical polymerization (SI-ATRP) of sodium methacrylate (NaMA) and their use as substrates for the mineralization of calcium carbonate. A C ...

American Chemical Society2007

Personalized predictions of adverse side effects of the COVID-19 vaccines

Nahal Mansouri, Sahand Jamal Rahi

Background: Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was ...

ELSEVIER SCI LTD2023

Dataset for the publication "Reversal of nanomagnets by propagating magnons in ferrimagnetic yttrium iron garnet enabling nonvolatile magnon memory"

Dirk Grundler, Korbinian Baumgärtl

Raw data associated to the manuscript ‘’Reversal of nanomagnets by propagating magnons in ferrimagnetic yttrium iron garnet enabling nonvolatile magnon memory‘’, Nature Communications (2023); doi: https://doi.org/10.1038/s41467-023-37078-8 Information abou ...

Zenodo2023

Reproducibility Dataset for CRYOWRF v1.0

Michael Lehning, Varun Sharma, Franziska Gerber

This repository contains data required for reproducibility of the results to be published in the associated manuscript. Apart from reproducibility, the attached datasets also serve as templates for new users to adopt CRYOWRF in their research. The datasets ...

2023

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

Vassily Hatzimanikatis, Ljubisa Miskovic, Subham Choudhury, Michaël Roger Germain Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al (https://doi.org/10.1101/2023. ...

Zenodo2023

Data-based model maintenance in the era of industry 4.0: A methodology

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos

Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A co ...

ELSEVIER SCI LTD2022