Emma Finn

Emma Lucia Byrnes Finn

Harvard University

About Me

I’m an undergraduate at Harvard studying Mathematics and Classics, with an A.M. in Statistics through the concurrent AB/AM program. My work spans probability theory, statistical modeling, and machine learning—especially interpretable models, stochastic processes, and the mathematics of diffusion.

I’m currently writing two senior theses—one in Statistics on interpretable diffusion models and one in Classics exploring ancient mathematical thought in Greek historiography.



Publications, Blogs, and Resources

Origins of Creativity in Attention-Based Diffusion Models

Emma Finn, et al.

ICML 2025 Workshop on High-Dimensional Learning Dynamics. Explores how attention-enhanced score matching uncovers the mechanisms behind creativity in diffusion models. Read on arXiv

Mathematical Foundations of Interpretable Diffusion

Emma Finn · Math Thesis (2025–26)

Investigating the expressive power of different function classes as score networks in generative diffusion models, with a focus on interpretability and learning dynamics.

Coming Soon

Quantifying the Past: Empirical Tropes in Greek Historiography

Emma Finn · Classics Thesis (2025–26)

A study of how Herodotus, Thucydides, and Xenophon employ quantification as a rhetorical device within their historical narratives.

Coming Soon

Learning Artistic Signatures: Symmetry Discovery and Style Transfer

Emma Finn

We propose and validate a mathematically grounded definition of artistic style as global symmetries over local textures.

Read on arXiv.

Rader's Algorithm for the Fast Fourier Transform

Emma Finn

Junior Paper in Mathematics. Expository paper on the abstract algebra behind the FFT.

Rader's Fast Fourier Transform

Score and Structure

Emma Finn

A blog exploring the intersections of algebraic structures and statistical inference, with visual examples and applications.

Read the Blog

Education

  • A.M. in Statistics (intended), Harvard University, May 2026
  • A.B. in Mathematics and Classics, Harvard University, May 2026

Teaching

  • Fall 2025: Statistics 210 – Graduate Probability I (TF)
  • Spring 2025: Statistics 111 – Introduction to Statistical Inference (TF)
  • Fall 2024: Statistics 110 – Introduction to Probability (TF)
  • Spring 2024: Math 21B – Linear Algebra and Differential Equations (CA)
  • Fall 2023: Math 21A – Multivariable Calculus (CA)

Other

I love to read, bake (mostly scones and foccacia), and run (slowly!). I’m also a huge NYT-connections enthusiast. If you have advice on surviving your first marathon, please drop me a line!


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