23 citations · 39 across the 6 of their papers we have counts for
6 papers
LGEM: a first-order logic framework for automated improvement of metabolic network models through abduction
Alexander H. Gower, Konstantin Korovin, Daniel Brunnsåker +2
Scientific discovery in biology is difficult due to the complexity of the systems involved and the expense of obtaining high quality experimental data. Automated techniques are a p…
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems
Stefan Kramer, Mattia Cerrato, Jannis Brugger +2
The paper surveys automated scientific discovery, from equation discovery and symbolic regression to autonomous discovery systems and agents. It discusses the individual approaches…
Transformative Machine Learning
Ivan Olier, Oghenejokpeme I. Orhobor, Joaquin Vanschoren +1
The key to success in machine learning (ML) is the use of effective data representations. Traditionally, data representations were hand-crafted. Recently it has been demonstrated t…
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
Ivan Olier, Noureddin Sadawi, G. Richard Bickerton +4
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study of meta-learning. This application area is of the highest societal importance,…
Computing exponentially faster: Implementing a nondeterministic universal Turing machine using DNA
Andrew Currin, Konstantin Korovin, Maria Ababi +4
The theory of computer science is based around Universal Turing Machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical em…
Qualitative System Identification from Imperfect Data
George M. Coghill, Ross D. King, Ashwin Srinivasan
Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to m…