Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that answer questions, diagnose diseases, recommend music and ...

Background Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year ...

Abstract: Originally, GenProg was created to repair buggy programs written in the C programming language, launching a new discipline in Generate-and-Validate approach of Automated Program Repair (APR) ...

hal-cgp is an extensible pure Python library implementing Cartesian genetic programming to represent, mutate and evaluate populations of individuals encoding symbolic expressions targeting ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Antimicrobial peptides (AMPs) have emerged as a promising alternative to conventional ...

Despite decades of investigation, brain tumors remain among the most lethal and debilitating malignancies of all forms 1. Glioma, the most common variant of brain tumors in the adult population, has ...

Neuromorphic computing technologies are about to change modern computing, yet most work thus far has emphasized hardware development. This review focuses on the latest progress in algorithmic advances ...

Quantum hardware is prone to errors and quantum error correction is a fundamental technique in quantum computing. We present an automated method to synthesize ...

This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...

In computing, we have a great diversity of tools at our disposal to perform any given task. We know many different sorting algorithms, cache eviction policies, hash functions, compression algorithms, ...

Generative AI models use prompts to guide content generation and use transfer learning to become more proficient. Early genAI models were built with specific data types and applications in mind. For ...