Publications related to Recognizing And Utilizing Novel Research Opportunities With Artificial Intelligence

Related publications (19)

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, Shuguang Yuan, Dongchun Ni, Babatunde Edukpe Ekundayo

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

2024

Electronic Excited States from Physically Constrained Machine Learning

Michele Ceriotti, Jigyasa Nigam, Divya Suman

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

2024

HYBRIDMINDS-summary and outlook of the 2023 international conference on the ethics and regulation of intelligent neuroprostheses

Marcello Ienca, Georg Michael Joachim Starke

Neurotechnology and Artificial Intelligence (AI) have developed rapidly in recent years with an increasing number of applications and AI-enabled devices that are about to enter the market. While promising to substantially improve quality of life across var ...

FRONTIERS MEDIA SA2024

Measurement of the cross section of top quark-antiquark pair production in association with a W boson in proton-proton collisions at √s=13 TeV

Jan Steggemann, Konstantin Androsov, Anna Mascellani, Joanna Malgorzata Wanczyk

The production of a top quark-antiquark pair in association with a W boson (t (t) over barW) is measured in proton-proton collisions at a center-of-mass energy of 13TeV. The analyzed data was recorded by the CMS experiment at the CERN LHC and corresponds ...

Springer Nature2023

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

Alexandre Massoud Alahi, Simon Elias Bibri, Amin Kaboli

The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart c ...

Elsevier2023

Regulating Artificial Intelligence in the EU, United States and China - Implications for energy systems

Ali Hariri

The growing prevalence and potential impact of artificial intelligence (AI) on society rises the need for regulation. In return, the shape of regulations will affect the application potential of AI across all economic sectors. This study compares the appro ...

IEEE Computer Society2023

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

Emmanuel Abbé, Thabodhan Mahendiran

Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correct ...

Oxford Univ Press2023

Review on Uric Acid Recognition by MOFs with a Future in Machine Learning

Shaswati Mandal

Uric acid (UA) is produced from purine metabolism and serves as a prevalent biomarker for multiple diseases including cancer. Hyperuricemia or hypouricemia can cause multiple dysfunctions throughout the biological processes. Consequently, there is a pressi ...

Amer Chemical Soc2023

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

Georg Michael Joachim Starke

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

Multi-Level Participatory GIS Framework to Assess Mobility Needs and Transport Barriers in Rural Areas: A Case Study of Rural Mumias East, a Sub-County of Kakamega, Kenya

Jérôme Chenal, Pablo Txomin Harpo de Roulet

In recent decades, there has been a growing interest in the application of GIS to community empowerment or new policy development through participatory design, information gathering and implementation. This study, therefore, aims to apply a multi-level par ...

MDPI AG2023

Bacterial nanopores open the future of data storage

Aleksandra Radenovic, Matteo Dal Peraro, Chan Cao, Lucien Fabrice Krapp, Alissa Agerova

In the era of "big data" finding solutions for data storage alternative to those based on silicon or magnetic tapes is an urgent need for our society. The development of polymers that can store information at the molecular level has opened up new opportuni ...

IEEE2022

Page Layout Analysis of Text-heavy Historical Documents: a Comparison of Textual and Visual Approaches

Matteo Romanello, Sven Nicolas Yoann Najem-Meyer

Page layout analysis is a fundamental step in document processing which enables to segment a page into regions of interest. With highly complex layouts and mixed scripts, scholarly commentaries are text-heavy documents which remain challenging for state-of ...

2022

3D Structure From 2D Microscopy Images Using Deep Learning

Suliana Manley, Christian Sieben

Understanding the structure of a protein complex is crucial in determining its function. However, retrieving accurate 3D structures from microscopy images is highly challenging, particularly as many imaging modalities are two-dimensional. Recent advances i ...

Frontiers Media Sa2021

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Virginie Janine Camille Lurkin, Timothy Michael Hillel, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2021

Pretraining boosts out-of-domain robustness for pose estimation

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Steffen Schneider

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

Digital approaches and mobilities in the Big Data era

Jean-François Lucas

This chapter discusses some of the opportunities offered by Big Data to understand mobility practices. However, beyond its promises, it has to be considered as human and social constructions. Therefore, the author underlines the importance of describing al ...

Routledge, Taylor & Francis2020

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

Olivier Sauter, Alessandro Pau

In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...

TAYLOR & FRANCIS INC2020

Lyrics-Conditioned Neural Melody Generation

Simon Canales

Generating melody from lyrics to compose a song has been a very interesting research topic in the area of artificial intelligence and music, which tries to predict generative music relationship between lyrics and melody. In this demonstration paper, by exp ...

SPRINGER INTERNATIONAL PUBLISHING AG2020

Towards Open Data in Digital Education Platforms

Denis Gillet, Maria Jesus Rodriguez Triana, Juan Carlos Farah, Joana Catarina Soares Machado

Despite the traction gained by the open data movement and the rise of big data and learning analytics in education, there is limited support for researchers in education to generate, access, and share experimental data using openly-available digital educat ...

IEEE2019