Lara Thompson

Yet another physicist doing ML.

Embeddings (Jul 2023):
Some introductory notes on embeddings are pre-reading for our data science paper reading group.
How Bad is Top-K Recommendation under Competing Content Creators? (Jul 2023):
Some backround notes on recommenders from a game theory / bandit learning perspective.
Assess Yourself for Better Bouldering (Dec 2021):
Analysis of a climbing survey dataset to test the wisdom of the crowd in how best to improve at climbing and assess training progress.
Data is everywhere! (Sep 2020):
Last night I was on a data science career panel (of awesome ladies!) as part the Vancouver Datajam 2020 and I promised (as I've been meaning to do for a while...) to post a list of data resources.
GPU for ML only on Ubuntu (Sep 2020):
To go against the grain, you have to fight.
Site overhaul to get ~~rid of~~ Jekyll (Sep 2020):
If you know html+css, why use a framework? Turns out, a few reasons.
Linear Regression with Uncertainty (Sep 2020):
Everyone uses linear regression whether they admit it or not. Here I review the math behind it with estimates of uncertainty.
Learning to learn without forgetting: a summary (Aug 2019):
Bullet-point form summary of this excellent paper. Contributions include a memory store of past examples; balances learning of new updates with recall of these stored examples; continual (online) learning in supervised and reinforcement learning settings.