Publications

Narayanan Kasthuri, Kenneth Jeffrey Hayworth, Daniel Raimund Berger, Richard Lee Schalek, José Angel Conchello, Seymour Knowles-Barley, Dongil Lee, Amelio Vázquez-Reina, Verena Kaynig, Thouis Raymond Jones, Mike Roberts, Josh Lyskowski Morgan, Juan Carlos Tapia, H Sebastian Seung, William Gray Roncal, Joshua Tzvi Vogelstein, Randal Burns, Daniel Lewis Sussman, Carey Eldin Priebe, Hanspeter Pfister, Jeff William Lichtman (2015). Saturated Reconstruction of a Volume of Neocortex. Cell.
DOI
Daniel L Sussman, Alexander Volfovsky, Edoardo M Airoldi (2015). Analyzing statistical and computational tradeoffs of estimation procedures. arxiv.
Arxiv
Vince Lyzinski, Daniel L Sussman, Minh Tang, Avanti Athreya, Carey E Priebe (2014). Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding. Electronic journal of statistics.
Arxiv DOI
Daniel Lewis Sussman (2014). Foundations of adjacency spectral embedding.
URL
Daniel L Sussman, Minh Tang, Carey E Priebe (2014). Consistent latent position estimation and vertex classification for random dot product graphs. IEEE transactions on pattern analysis and machine intelligence.
Arxiv DOI
Minh Tang, Daniel L Sussman, Carey E Priebe (2013). Universally consistent vertex classification for latent positions graphs. Annals of statistics.
Arxiv DOI
Li Chen, Douglas C Comer, Carey E Priebe, Daniel Sussman, James C Tilton (2013). Refinement of a Method for Identifying Probable Archaeological Sites from Remotely Sensed Data. Mapping Archaeological Landscapes from Space.
DOI
D L Sussman, D Mhembere, S Ryman, R Jung, Others (2013). Massive Diffusion MRI Graph Structure Preserves Spatial Information. Organization for Human.
DOI
Donniell E Fishkind, Daniel L Sussman, Minh Tang, Joshua T Vogelstein, Carey E Priebe (2013). Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown. SIAM Journal on Matrix Analysis and Applications.
Arxiv DOI
D Mhembere, W Gray Roncal, D Sussman, C E Priebe, R Jung, S Ryman, R J Vogelstein, J T Vogelstein, R Burns (2013). Computing scalable multivariate glocal invariants of large (brain-) graphs. 2013 IEEE Global Conference on Signal and Information Processing.
DOI