Scott Linderman
Scott Linderman
Verified email at stanford.edu - Homepage
TitleCited byYear
Discovering Latent Network Structure in Point Process Data
SW Linderman, RP Adams
Proceedings of The 31st International Conference on Machine Learning, 1413–1421, 2014
1792014
The striatum organizes 3D behavior via moment-to-moment action selection
JE Markowitz, WF Gillis, CC Beron, SQ Neufeld, K Robertson, ND Bhagat, ...
Cell 174 (1), 44-58. e17, 2018
792018
Variational sequential monte carlo
CA Naesseth, SW Linderman, R Ranganath, DM Blei
arXiv preprint arXiv:1705.11140, 2017
762017
Bayesian learning and inference in recurrent switching linear dynamical systems
S Linderman, M Johnson, A Miller, R Adams, D Blei, L Paninski
Artificial Intelligence and Statistics, 914-922, 2017
65*2017
Reparameterization gradients through acceptance-rejection sampling algorithms
CA Naesseth, FJR Ruiz, SW Linderman, DM Blei
arXiv preprint arXiv:1610.05683, 2016
56*2016
Dependent multinomial models made easy: Stick-breaking with the Pólya-Gamma augmentation
S Linderman, MJ Johnson, RP Adams
Advances in Neural Information Processing Systems, 3456-3464, 2015
512015
Learning latent permutations with gumbel-sinkhorn networks
G Mena, D Belanger, S Linderman, J Snoek
arXiv preprint arXiv:1802.08665, 2018
462018
Reparameterizing the birkhoff polytope for variational permutation inference
SW Linderman, GE Mena, H Cooper, L Paninski, JP Cunningham
arXiv preprint arXiv:1710.09508, 2017
302017
A Bayesian nonparametric approach for uncovering rat hippocampal population codes during spatial navigation
SW Linderman, MJ Johnson, MA Wilson, Z Chen
Journal of neuroscience methods 263, 36-47, 2016
29*2016
Scalable bayesian inference for excitatory point process networks
SW Linderman, RP Adams
arXiv preprint arXiv:1507.03228, 2015
272015
Bayesian latent structure discovery from multi-neuron recordings
S Linderman, RP Adams, JW Pillow
Advances in Neural Information Processing Systems, 2002-2010, 2016
252016
Bayesian latent structure discovery from multi-neuron recordings
S Linderman, RP Adams, JW Pillow
Advances in Neural Information Processing Systems, 2002-2010, 2016
252016
A framework for studying synaptic plasticity with neural spike train data
S Linderman, CH Stock, RP Adams
Advances in neural information processing systems, 2330-2338, 2014
152014
Tree-structured recurrent switching linear dynamical systems for multi-scale modeling
J Nassar, SW Linderman, M Bugallo, IM Park
arXiv preprint arXiv:1811.12386, 2018
102018
Using computational theory to constrain statistical models of neural data
SW Linderman, SJ Gershman
Current opinion in neurobiology 46, 14-24, 2017
92017
Cross-corpora unsupervised learning of trajectories in autism spectrum disorders
HM Elibol, V Nguyen, S Linderman, M Johnson, A Hashmi, F Doshi-Velez
The Journal of Machine Learning Research 17 (1), 4597-4634, 2016
72016
Point process latent variable models of larval zebrafish behavior
A Sharma, R Johnson, F Engert, S Linderman
Advances in Neural Information Processing Systems, 10919-10930, 2018
62018
Bayesian inference for latent Hawkes processes
SW Linderman, Y Wang, DM Blei
Advances in Neural Information Processing Systems, 2017
62017
Probabilistic models of larval zebrafish behavior: structure on many scales
RE Johnson, S Linderman, T Panier, CL Wee, E Song, KJ Herrera, ...
bioRxiv, 672246, 2019
52019
Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C. elegans
SW Linderman, ALA Nichols, DM Blei, M Zimmer, L Paninski
bioRxiv, 621540, 2019
52019
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Articles 1–20