no code implementations • 9 Jul 2023 • Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Jon Rowe, James Evans, Hiroaki Kitano, Ross King
Yet, AI has contributed less to fundamental science in part because large data sets of high-quality data for scientific practice and model discovery are more difficult to access.
1 code implementation • ICLR 2023 • Anuj Daga, Sumeer Ahmad Khan, David Gomez Cabrero, Robert Hoehndorf, Narsis A. Kiani, Jesper Tegnér
The LEP-AD model scales favorably in performance with the size of training data.
Ranked #1 on Protein Language Model on DAVIS-DTA
no code implementations • 7 Oct 2019 • Santiago Hernández-Orozco, Hector Zenil, Jürgen Riedel, Adam Uccello, Narsis A. Kiani, Jesper Tegnér
We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research.
2 code implementations • 9 Jul 2018 • C. -H. Huck Yang, Rise Ooi, Tom Hiscock, Victor Eguiluz, Jesper Tegnér
We ask whether larger dynamical network motifs exist in biological networks, thus contributing to the higher-order organization of a network.
no code implementations • 18 Feb 2018 • Hector Zenil, Narsis A. Kiani, Allan A. Zea, Jesper Tegnér
Complex data usually results from the interaction of objects produced by different generating mechanisms.
2 code implementations • 16 Feb 2018 • Hector Zenil, Narsis A. Kiani, Antonio Rueda-Toicen, Allan A. Zea, Jesper Tegnér
We introduce a family of unsupervised, domain-free, and (asymptotically) model-independent algorithms based on the principles of algorithmic probability and information theory designed to minimize the loss of algorithmic information, including a lossless-compression-based lossy compression algorithm.
Data Structures and Algorithms Information Theory Information Theory Physics and Society
no code implementations • 15 Sep 2017 • Hector Zenil, Narsis A. Kiani, Francesco Marabita, Yue Deng, Szabolcs Elias, Angelika Schmidt, Gordon Ball, Jesper Tegnér
We demonstrate that the algorithmic information content of a system is deeply connected to its potential dynamics, thus affording an avenue for moving systems in the information-theoretic space and controlling them in the phase space.
no code implementations • 21 Sep 2015 • Hector Zenil, James A. R. Marshall, Jesper Tegnér
Being able to objectively characterise the intrinsic complexity of behavioural patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems.
no code implementations • 24 Aug 2015 • Hector Zenil, Angelika Schmidt, Jesper Tegnér
Here we further unpack ideas related to computability, algorithmic information theory and software engineering, in the context of the extent to which biology can be (re)programmed, and with how we may go about doing so in a more systematic way with all the tools and concepts offered by theoretical computer science in a translation exercise from computing to molecular biology and back.
no code implementations • 17 Jan 2015 • Nicolas Gauvrit, Hector Zenil, Jesper Tegnér
We survey concepts at the frontier of research connecting artificial, animal and human cognition to computation and information processing---from the Turing test to Searle's Chinese Room argument, from Integrated Information Theory to computational and algorithmic complexity.