1 citations · 1 across the 2 of their papers we have counts for
5 papers
The influence of the random numbers quality on the results in stochastic simulations and machine learning
Benjamin A. Antunes
Pseudorandom number generators (PRNGs) are ubiquitous in stochastic simulations and machine learning (ML), where they drive sampling, parameter initialization, regularization, and…
Statistical Quality and Reproducibility of Pseudorandom Number Generators in Machine Learning technologies
Benjamin A. Antunes
Machine learning (ML) frameworks rely heavily on pseudorandom number generators (PRNGs) for tasks such as data shuffling, weight initialization, dropout, and optimization. Yet, the…
Reproducibility, energy efficiency and performance of pseudorandom number generators in machine learning: a comparative study of python, numpy, tensorflow, and pytorch implementations
Benjamin Antunes, David R. C Hill
Pseudo-Random Number Generators (PRNGs) have become ubiquitous in machine learning technologies because they are interesting for numerous methods. The field of machine learning hol…
Reproducibility, Replicability, and Repeatability: A survey of reproducible research with a focus on high performance computing
Benjamin A. Antunes, David R. C. Hill
Reproducibility is widely acknowledged as a fundamental principle in scientific research. Currently, the scientific community grapples with numerous challenges associated with repr…
Identifying Quality Mersenne Twister Streams For Parallel Stochastic Simulations
Benjamin Antunes, Claude Mazel, David R. C Hill
The Mersenne Twister (MT) is a pseudo-random number generator (PRNG) widely used in High Performance Computing for parallel stochastic simulations. We aim to assess the quality of…