#automatic differentiation

Differential Machine Learning at Bloomberg

I will be delivering the keynote at Bloomberg’s Quant Seminar in NYC next week, June 22th 2022, 17:00. The event can be followed in person or virtually. Registration is free but mandatory. Here is the registration link: https://go.bloomberg.com/attend/invite/bloombergquant-bbq-seminar-june2022/ In this event hosted by Bruno Dupire at Bloomberg’s headquarters, I will present advances in…

Risk podcast : Differential Machine Learning

Co-author Brian Huge and I were interviewed by Risk Magazine last week and got a chance to present differential ML and related algorithms in non-technical terms. The podcast is publicly available https://www.risk.net/cutting-edge/views/7880346/podcast-huge-and-savine-on-turbo-charging-derivatives-pricing Podcast: Huge and Savine on turbo-charging derivatives pricing

Axes that matter: PCA with a difference, Risk, 2021

Brian Huge and Antoine Savine, Risk, October 2021

Dimension Reduction Done Right -- presenting the upcoming (October 2021) Risk article: 'Axes that matter: PCA with a difference'

Differential Machine Learning: regression and PCA Presenting the upcoming (October 2021) Risk article ‘Axes that matter: PCA with a difference’

Differential regression illustrates the main ideas of differential machine learning, and demonstrates its power in a very simple context. We posted a small article with code on Google Colab, run it here: https://colab.research.google.com/github/differential-machine-learning/notebooks/blob/master/DifferentialRegression.ipynb

Modern Computational Finance: Parts I and II free on SSRN for a limited time

Free on SSRN for a limited time: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3735414

parts i and ii free for a limited time on SSRN

The first two parts (out of three) of my book Modern Computational Finance (Wiley, 2018) are complimentarily available on SSRN only in December 2020.

Part I teaches necessary C++ foundations with a focus on parallel computing. Part II summarizes the…

Differential Machine Learning, Risk, 2020

Brian Huge and Antoine Savine, Risk, October 2020