Sam Bowyer
I'm a probabilistic machine learning PhD student at the University of Bristol's Compass CDT. My research interests include probabilistic programming, deep learning, and using traditional statistics to improve LLM eval procedures. I've just finished an internship working on pretraining evals @ Cohere and will be rejoining full-time in September!
- links
- blog posts
- Bayesian LLM Finetuning (Compass Student Blog)
- Compass at AIUK 2025
- Special Report: Compass Away Day 2024
- presentations
- projects
- mrmr_eval -- a minimal tutorial on using mRMR for efficient LLM benchmarking
- bayes_evals -- a lightweight library for Bayesian analysis of LLM evals
- alan -- a massively parallel probabilistic programming language
- papers
- Efficient Benchmarking Is Just Feature Selection and Multiple Regression (preprint)
- Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference (ICLR 2026 DeLTa Workshop)
- Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints (ICML 2025 Spotlight)
- Massively Parallel Expectation Maximization For Approximate Posteriors (AABI 2025)
- Using Using Autodiff to Estimate Posterior Moments, Marginals and Samples (UAI 2024)
- tennis