Physical principles for scalable neural recording. - Adam H. Marblestone; Bradley M. Zamft; Yael Maguire; Mikhail G. Shapiro; Thaddeus Cybulski; Joshua I. Glaser; Dario Amodei; P. Benjamin Stranges; Reza Kalhor; David Dalrymple; Dongjin Seo; Elad Alon; et al. (Frontiers Comput. Neurosci., 2013)

Statistical Analysis of Molecular Signal Recording. - Joshua I. Glaser; Bradley M. Zamft; Adam H. Marblestone; Jeffrey R. Moffitt; Keith E. J. Tyo; Edward S. Boyden III; George M. Church; Konrad P. Körding (PLoS Comput. Biol., 2013)

Spatial information in large-scale neural recordings. - Thaddeus Cybulski; Joshua I. Glaser; Adam Henry Marblestone; Bradley M. Zamft; Edward S. Boyden III; George M. Church; Konrad P. Körding (Frontiers Comput. Neurosci., 2014)

Puzzle Imaging: Using Large-scale Dimensionality Reduction Algorithms for Localization. - Joshua I. Glaser; Bradley M. Zamft; George M. Church; Konrad P. Körding (CoRR, 2015)

The Development and Analysis of Integrated Neuroscience Data. - Joshua I. Glaser; Konrad P. Körding (Frontiers Comput. Neurosci., 2016)

Machine learning for neural decoding. - Joshua I. Glaser; Raeed H. Chowdhury; Matthew G. Perich; Lee E. Miller; Konrad P. Körding (CoRR, 2017)

The Roles of Supervised Machine Learning in Systems Neuroscience. - Joshua I. Glaser; Ari S. Benjamin; Roozbeh Farhoodi; Konrad P. Körding (CoRR, 2018)

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations. - Joshua I. Glaser; Matthew R. Whiteway; John P. Cunningham; Liam Paninski; Scott W. Linderman (NeurIPS, 2020)

Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI. - Jesse A. Livezey; Joshua I. Glaser (CoRR, 2020)

Deep learning approaches for neural decoding across architectures and recording modalities. - Jesse A. Livezey; Joshua I. Glaser (Briefings Bioinform., 2021)

Switching Autoregressive Low-rank Tensor Models. - Hyun Dong Lee; Andrew Warrington; Joshua I. Glaser; Scott W. Linderman (NeurIPS, 2023)