Differential Machine Learning by Brian Huge & Antoine Savine
differential-machine-learning
Demonstration notebooks and additional material for the Risk articles on differential machine learning by Brian Huge and Antoine Savine (2020-2021)
Danske Bank Copenhagen
Yiwei Yang
vickiegpt
Ph.D. student @SlugLab, try to make the system fast and reliable.
Baskin Engineering Santa Cruz, California
Shangtong Zhang
ShangtongZhang
Assistant Professor at UVA
University of Virginia Charlottesville, VA, United States
Sebastian Starke
sebastianstarke
Research Scientist @ Meta, PhD @ UoE. Formerly @ Electronic Arts, Adobe Research. Enjoying coffee and life in no particular order.
London, UK
Mark Rousskov
Mark-Simulacrum
Rust project release team lead & infra member (amongst other roles).
Jon Gjengset
jonhoo
Rust educational streamer. At @helsing-ai. Previously at AWS. A fan of making things secure, fast, scalable, and well-documented.
@helsing-ai Oslo, Norway
chris m
quietlychris
Particularly enjoys Rust, and is interested in highly-reliable systems, robotics, and machine learning
John Goodacre
jsg71
Ex Morgan Stanley fund manager, and hedge fund mathmo looking at machine learning in finance.
Patrick Kidger
patrick-kidger
ML+proteins, sciML, numerics, neural ODEs ╱ building 'scipy w/ autodiff+GPU' in JAX: Equinox, Diffrax, Lineax, etc ╱ solo traveller, martial artist, scuba diver
Cradle.bio Zürich
Zack Chase Lipton
zackchase
Assistant Professor of Machine Learning & Operations Research (CMU).
CMU, Amazon Pittsburgh
Vivek Palaniappan
VivekPa
Keen on finding effective solutions to complex problems - looking into the broad intersection between engineering, finance and AI.
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