References

Adam: A Method for Stochastic Optimization

Diederik P. Kingma & Jimmy Ba (2014)

arXiv.

DOI: https://doi.org/10.48550/arxiv.1412.6980

Abstract. Introduces Adam, which combines momentum (first-moment estimate) with RMSProp-style per-parameter scaling (second-moment estimate) and bias correction. Adam's robustness and default-friendly hyperparameters have made it the most widely used deep learning optimiser.

Tags: optimisation adam sgd

This site is currently in Beta. Contact: Chris Paton

Textbook of Usability · Textbook of Digital Health

Auckland Maths and Science Tutoring

AI tools used: Claude (research, coding, text), ChatGPT (diagrams, images), Grammarly (editing).