Publications

Zihuan Qiao, Daniel L Sussman (2021). iGraphMatch .
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Daniel L Sussman, Youngser Park, Carey E Priebe, Vince Lyzinski (2020). Matched Filters for Noisy Induced Subgraph Detection. IEEE transactions on pattern analysis and machine intelligence.
Arxiv DOI
Vince Lyzinski, Daniel L Sussman (2020). Matchability of heterogeneous networks pairs. Information and inference.
Arxiv DOI
Benjamin Draves, Daniel L Sussman (2020). Bias-Variance Tradeoffs in Joint Spectral Embeddings. arxiv.
Arxiv
K Pantazis, D L Sussman, Y Park, C E Priebe, V Lyzinski (2019). Multiplex graph matching matched filters. 2019 IEEE International Conference on Big Data (Big Data).
DOI
L Li, D L Sussman (2019). Graph Matching via Multi-Scale Heat Diffusion. 2019 IEEE International Conference on Big Data (Big Data).
DOI
Runze Tang, Michael Ketcha, Alexandra Badea, Evan D Calabrese, Daniel S Margulies, Joshua T Vogelstein, Carey E Priebe, Daniel L Sussman (2019). Connectome Smoothing via Low-Rank Approximations. IEEE transactions on medical imaging.
Arxiv DOI
Eric W Bridgeford, Daniel Sussman, Vince Lyzinski, Yichen Qin, Youngser Park, Brian Caffo (2018). What Is Connectome Coding?. SHORT COURSE 2: Functional, Structural, and Molecular Imaging, and Big Data Analysis.
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Fei Fang, Daniel L Sussman, Vince Lyzinski (2018). Tractable Graph Matching via Soft Seeding. arxiv.
Arxiv
Avanti Athreya, Donniell E Fishkind, Minh Tang, Carey E Priebe, Youngser Park, Joshua T Vogelstein, Keith Levin, Vince Lyzinski, Yichen Qin, Daniel L Sussman (2018). Statistical Inference on Random Dot Product Graphs: a Survey. Journal of machine learning research.
Arxiv DOI