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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

On subsets and orderings

8 minute read

Published:

If you’re using a recent version of SciPY you might be using this idea already and not even know.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Nearest-neighbor matchup effects: accounting for team matchups for predicting March Madness

Published in Journal of Quantitative Analysis in Sports, 2015

We introduce our novel nearest-neighbor matchup effects framework, which presents a flexible way to account for team characteristics above and beyond team strength that may influence game outcomes. The paper was covered by several media outlets, click into the page to see one example.

Recommended citation: Hoegh, A., Carzolio, M., Crandell, I., Hu, X., Roberts, L., Song, Y., & Leman, S. C. (2015). Nearest-neighbor matchup effects: accounting for team matchups for predicting March Madness. Journal of Quantitative Analysis in Sports, 11(1), 29-37.
Download Paper | Download Slides

Smart Vision-Language Reasoners

Published in ICML 2024, 2024

Images in Math AI Considered harmful? Not quite. This paper demonstrates improved performance on question answering problems in math by customizing the neural network architecture to pool information from both vision and text backbones. The improvements come from a custom QF layer which includes multihead self attention layers as well as a cross attention layer (vision & text). We fine tune the model using the smart-101 dataset presented in CVPR 2023.

Recommended citation: Roberts D, Roberts L. Smart Vision-Language Reasoners. arXiv preprint arXiv:2407.04212. 2024 Jul 5.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.