## Posters

- J. Browne et al. Forest Packing: Fast Parallel Decision Forests. 2019.
- J. Chung et al. Human Structural Connectomes are Heritable. 2019.
- B. D. Pedigo et al. GraSPy: an Open Source Python Package for Statistical Connectomics. 2019.
- S. Chen et al. A Sparse High Dimensional State-Space Model with an Application to Neuroimaging Data. 2015.
- S. Chen et al. High Dimensional State Space Model with L-1 and L-2 Penalties. 2015.
- F. Collman et al. An integrated imaging and staining platform for cubic millimeter scale array tomography. 2015.
- E. L. Deyer et al. X-Brain: Quantifying Mesoscale Neuroanatomy Using X-ray Microtomography. 2015.
- S. J. Smith et al. The Open Synaptome Project: Toward a Microscopy-Based Platform for Single-synapse Analysis of Diverse Populations of CNS Synapses. 2015.
- J. T. Vogelstein. Open Connectome Project & NeuroData: Enabling Data-Driven Neuroscience at Scale. 2015.
- S. Wang et al. Optimal Design for Discovery Science: Applications in Neuroimaging. 2015.
- S. Sikka et al. Towards automated analysis of connectomes: The configurable pipeline for the analysis of connectomes (c-pac). 2014.
- R. D. Airan, J. T. Vogelstein and others. Reproducible differentiation of individual of individual subjects with minimal acquisition time via resting state fMRI. 2013.
- C. Craddock and others. Towards Automated Analysis of Connectomes: The Configurable Pipeline for the Analysis of Connectomes. 2013.
- W. R. Gray and others. Towards a Fully Automatic Pipeline for Connectome Estimation from High-Resolution EM Data. 2013.
- D. Koutra et al. Are All Brains Wired Equally? 2013.
- D. Mhembere and others. Multivariate Invariants from Massive Brain-Graphs. 2013.
- E. A. Pnevmatikakis and others. Rank-penalized nonnegative spatiotemporal deconvolution and demixing of calcium inaging data. 2013.
- Y. Qin and others. Robust Clustering of Adjacency Spectral Embeddings of Brain Graph Data via Lq-Likelihood. 2013.
- N. Sismanis and others. Feature Clustering from a Brain Graph for Voxel-to-Region Classification. 2013.
- D. Sussman and others. Massive Diffusion MRI Graph Structure Preserves Spatial Information. 2013.
- J. T. Vogelstein and C. E. Priebe. Nonparametric Two-Sample Testing on Graph-Valued Data. 2013.
- J. T. Vogelstein and others. Anomaly Screening and Clustering of Multi-OBject Movies via Multiscale Structure Learning. 2013.
- W. R. Gray and others. Towards a Fully Automatic Pipeline for Connectome Estimation from High-Resolution EM Data. 2012.
- J. T. Vogelstein and others. Statistical Connectomics. 2012.
- J. T. Vogelstein and others. BRAINSTORM towards clinically and scientifically useful neuroimaging analytics. 2012.
- W. R. Gray et al. Magnetic resonance connectome automated pipeline and repeatability analysis. 2011.
- J. T. Vogelstein et al. Large graph classification: theory and statistical connectomics applications. 2011.
- J. T. Vogelstein et al. Connectome Classification using statistical graph theory and machine learning. 2011.
- J. T. Vogelstein et al. Connectome Classification: Statistical Graph Theoretic Methods for Analysis of MR-Connectome Data. 2011.
- J. T. Vogelstein et al. Open Connectome Project: collectively reverse engineering the brain one synapse at a time. 2011.
- J. T. Vogelstein et al. Dot product embedding in large (errorfully observed) graphs with applications in statistical connectomics. 2011.
- W. R. Gray et al. Graph-Theoretical Methods for Statistical Inference on MR Connectome Data. 2010.
- J. T. Vogelstein et al. Graph-Theoretical Methods for Statistical Inference on MR Connectome Data. 2010.
- J. T. Vogelstein et al. Towards Confirming Neural Circuit Inference from Population Calcium Imaging. 2010.
- J. T. Vogelstein et al. Towards Inferring Neural Circuit Inference from Population Calcium Imaging. 2010.
- J. T. Vogelstein et al. Measuring and reconstructing the brain at the synaptic scale: towards a biofidelic human brain in silico. 2010.
- J. T. Vogelstein, R. Vogelstein and C. E. Priebe. A Neurocognitive Graph-Theoretical Approach to Understanding the Relationship Between Minds and Brains. 2010.
- J. T. Vogelstein et al. Towards Confirming Neural Circuits from Population Calcium Imaging. 2009.
- J. T. Vogelstein et al. Towards Inferring Neural Circuit Inference from Population Calcium Imaging. 2009.
- J. T. B. Vogelstein and L. Paninski. Model-Based Optimal Inference of Spike-Times and Calcium Dynamics given Noisy and Intermittent Calcium-Fluorescence Imaging. 2008.
- J. T. Vogelstein et al. From Calcium Sensitive Fluorescence Movies to Spike Trains. 2008.
- J. T. Vogelstein and L. Paninski. Inferring Spike Trains, Learning Tuning Curves, and Estimating Connectivity from Calcium Imaging. 2008.
- J. T. Vogelstein et al. Inferring Spike Trains, Neural Filters, and Network Circuits from in vivo Calcium Imaging. 2007.
- J. T. Vogelstein et al. Maximum Likelihood Inference of Neural Dynamics under Noisy and Intermittent Observations using Sequential Monnte Carlo EM Algorithms. 2007.
- J. T. Vogelstein and K. Zhang. A novel theory for simultaneous representation of multiple dynamic states in hippocampus. 2004.
- J. T. Vogelstein et al. Up-down asymmetry in memory guided saccadic eye movements are independent of head orientation in space. 2002.
- J. T. Vogelstein et al. Up-down asymmetry in memory guided saccadic eye movements are independent of head orientation in space. 2002.