research highlights
- JT Vogelstein, et al. Fast Inexact Graph Matching with Applications in Connectomics. arxiv, code, repo, Submitted to IEEE PAMI.
- JT Vogelstein, et al. Shuffled Graph Classification: Theory and Applications in Statistical Connectomics. arxiv, repo, Submitted to IEEE PAMI.
- JT Vogelstein, et al. Graph Classification using Signal Subgraphs: Applications in Statistical Connectomics. Submitted. arxiv, code, repo.
philosophy
This world is already an incredibly beautiful and lovely place to live (for many of us). Our thesis is that by improving our models of how we think and act, we will be able to make this world even better for more of us. More specifically, we aim to contribute by developing and applying tools from statistics to neuroscience, psychology, and beyond. Our primary foci are statistical graph theory and brain-graphs (connectomes).
Perhaps partially because we fervently believe that we are all in this together, we are strong advocates of open-science, that is, making one's research freely available to all. To that end, all our work is open, meaning our code is open source and all the data we use is open access. The intention of this website is to share our dreams, our work, and invite you to come join our party, and perhaps inspire others to unify their dreams and their realities.