Search · four archives
Search · four archives
13 papers · ranked by Valyu relevance
Fan Yang, Xiaojuan Zhang, Zhiwen Yu, Chao Liu
Deep learning has been broadly applied in many fields and has greatly improved efficiency compared to traditional approaches. However, it cannot resolve issues well when there are a lack of training samples, or in some varying cases, it cannot give a clear output. Human beings and machines that work in a collaborative…
Stefano Teso, Öznur Alkan, Wolfgang Stammer, Elizabeth Daly
Explanations have gained an increasing level of interest in the AI and Machine Learning (ML) communities in order to improve model transparency and allow users to form a mental model of a trained ML model. However, explanations can go beyond this one way communication as a mechanism to elicit user control, because once…
Nicolas Pfeuffer, Lorenz Baum, Wolfgang Stammer, Benjamin M. Abdel-Karim + 6 more
'Benjamin M. Abdel-Karim' 'Patrick Schramowski' 'Andreas M. Bucher' 'Christian Hügel' 'Gernot Rohde' 'Kristian Kersting' 'Oliver Hinz'] The most promising standard machine learning methods can deliver highly accurate classification results, often outperforming standard white-box methods. However, it is hardly possible…
Hubert Baniecki, Dariusz Parzych, Przemyslaw Biecek
The growing need for in-depth analysis of predictive models leads to a series of new methods for explaining their local and global properties. Which of these methods is the best? It turns out that this is an ill-posed question. One cannot sufficiently explain a black-box machine learning model using a single method…
Carlos Celemin, Jens Kober
In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they make mistakes influenced by diverse human factors. In this…
Shrouk H. Hessen, Hatem M. Abdul-kader, Ayman E. Khedr, Rashed K. Salem
'Rashed K. Salem'] Recently, artificial intelligence (AI) domain increased to contain finance, education, health, mining, and education. Artificial intelligence controls the performance of systems that use new technologies, especially in the education environment. The multiagent system (MAS) is considered an…
Yi Yu
In today’s rapidly changing economy, efficient lifestyle has become the current situation of most mobile product users. With the development of performance tools and technologies, a fast lifestyle has brought more wealth and opportunities to users. The slow pace and fluctuating time are indirect income losses, which…
David Sidak, Jana Schwarzerová, Wolfram Weckwerth, Steffen Waldherr
Machine learning has become a powerful tool for systems biologists, from diagnosing cancer to optimizing kinetic models and predicting the state, growth dynamics, or type of a cell. Potential predictions from complex biological data sets obtained by “omics” experiments seem endless, but are often not the main objective…
Sathana Dushyanthen, Frances Hooley, Kayley Lyons, Jon Parkinson + 5 more
Background Global classrooms transcend geographical boundaries, fostering collaboration and knowledge exchange among learners worldwide. Artificial intelligence (AI) has the potential to enhance patient care, streamline processes, and revolutionise healthcare capabilities. However, there is a shortage of a skilled…
Zulema Udaondo
The exponential growth of biological data is one of the most significant trends observed in life sciences over the last few decades. Rapid technological changes and price reduction of new technologies have made omic approaches much more affordable to undertake experiments that generate vast quantities of data. In the…
Sandra Eloranta, Magnus Boman
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use. In an introduction to predictive modelling using machine learning, we conducted…
Adam J. Gormley
For decades, drug delivery scientists have been performing trial-and-error experimentation to manually sample parameter spaces and optimize release profiles through rational design. To enable this approach, scientists spend much of their career learning nuanced drug-material interactions that drive system behavior. In…
Cheng Xu, Ling-Yun Zhao, Cun-Si Ye, Ke-Chen Xu + 1 more
With the development of artificial intelligence(AI) in computer science and statistics, it has been further applied to the medical field. These applications include the management of infectious diseases, in which machine learning has created inroads in clinical microbiology, radiology, genomics, and the analysis of…