7 papers
Tighter Bounds for Algorithmic Complexity Estimation Using a Reusable Code-Based Block Decomposition Method
Eduardo Yuji Sakabe, Felipe S. Abrahão, Santiago Hernández-Orozco +2
The Block Decomposition Method (BDM) was introduced as an alternative to popular lossless compression methods such as LZW for estimating algorithmic complexity from the principles…
Integrative Adaptive Indexes from Noisy Routine Haematological Markers can Predict and Discriminate Health Status and Biological Age
Santiago Hernández-Orozco, Abicumaran Uthamacumaran, Francisco Hernández-Quiroz +2
For more than two decades, advances in personalised medicine and precision healthcare have largely been based on genomics and other omics data. These strategies aim to tailor inter…
Advancing the Scientific Method with Large Language Models: From Hypothesis to Discovery
Yanbo Zhang, Sumeer A. Khan, Adnan Mahmud +10
With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scie…
Minimal Algorithmic Information Loss Methods for Dimension Reduction, Feature Selection and Network Sparsification
Hector Zenil, Narsis A. Kiani, Alyssa Adams +5
We present a novel, domain-agnostic, model-independent, unsupervised, and universally applicable Machine Learning approach for dimensionality reduction based on the principles of a…
An Optimal, Universal and Agnostic Decoding Method for Message Reconstruction, Bio and Technosignature Detection
Hector Zenil, Alyssa Adams, Felipe S. Abrahão +1
We present an agnostic signal reconstruction method for zero-knowledge one-way communication channels in which a receiver aims to interpret a message sent by an unknown source abou…
Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits
Jun Qi, Chao-Han Yang, Samuel Yen-Chi Chen +3
Quantum Machine Learning (QML) offers tremendous potential but is currently limited by the availability of qubits. We introduce an innovative approach that utilizes pre-trained neu…