default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDScott W. Linderman
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[i20]Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman, Dan Biderman, Scott W. Linderman:
Towards a theory of learning dynamics in deep state space models. CoRR abs/2407.07279 (2024)- [i19]Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman:
Towards Scalable and Stable Parallelization of Nonlinear RNNs. CoRR abs/2407.19115 (2024) - [i18]Yixiu Zhao, Jiaxin Shi, Lester Mackey, Scott W. Linderman:
Informed Correctors for Discrete Diffusion Models. CoRR abs/2407.21243 (2024) - [i17]Amber Hu, David M. Zoltowski, Aditya Nair, David Anderson, Lea Duncker, Scott W. Linderman:
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems. CoRR abs/2408.03330 (2024) - 2023
- [j2]Jay A. Hennig
, Sandra A. Romero Pinto, Takahiro Yamaguchi, Scott W. Linderman, Naoshige Uchida, Samuel J. Gershman:
Emergence of belief-like representations through reinforcement learning. PLoS Comput. Biol. 19(9) (2023) - [c31]Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman:
Simplified State Space Layers for Sequence Modeling. ICLR 2023 - [c30]Yixiu Zhao, Scott W. Linderman:
Revisiting Structured Variational Autoencoders. ICML 2023: 42046-42057 - [c29]Dieterich Lawson, Michael Li, Scott W. Linderman:
NAS-X: Neural Adaptive Smoothing via Twisting. NeurIPS 2023 - [c28]Hyun Dong Lee, Andrew Warrington, Joshua I. Glaser, Scott W. Linderman:
Switching Autoregressive Low-rank Tensor Models. NeurIPS 2023 - [c27]Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon:
Convolutional State Space Models for Long-Range Spatiotemporal Modeling. NeurIPS 2023 - [i16]Yixiu Zhao, Scott W. Linderman:
Revisiting Structured Variational Autoencoders. CoRR abs/2305.16543 (2023) - [i15]Hyun Dong Lee, Andrew Warrington, Joshua I. Glaser, Scott W. Linderman:
Switching Autoregressive Low-rank Tensor Models. CoRR abs/2306.03291 (2023) - [i14]Dieterich Lawson, Michael Li, Scott W. Linderman:
NAS-X: Neural Adaptive Smoothing via Twisting. CoRR abs/2308.14864 (2023) - [i13]Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon:
Convolutional State Space Models for Long-Range Spatiotemporal Modeling. CoRR abs/2310.19694 (2023) - 2022
- [c26]Julia Costacurta, Lea Duncker, Blue Sheffer, Winthrop Gillis, Caleb Weinreb, Jeffrey E. Markowitz, Sandeep R. Datta, Alex H. Williams, Scott W. Linderman:
Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs. NeurIPS 2022 - [c25]Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman:
SIXO: Smoothing Inference with Twisted Objectives. NeurIPS 2022 - [i12]Yixin Wang, Anthony Degleris, Alex H. Williams, Scott W. Linderman:
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models. CoRR abs/2201.05044 (2022) - [i11]Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman:
SIXO: Smoothing Inference with Twisted Objectives. CoRR abs/2206.05952 (2022) - [i10]Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman:
Simplified State Space Layers for Sequence Modeling. CoRR abs/2208.04933 (2022) - 2021
- [c24]Libby Zhang, Tim Dunn, Jesse Marshall, Bence Olveczky, Scott W. Linderman:
Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model. AISTATS 2021: 2800-2808 - [c23]Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman:
Generalized Shape Metrics on Neural Representations. NeurIPS 2021: 4738-4750 - [c22]Jimmy T. H. Smith, Scott W. Linderman, David Sussillo:
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. NeurIPS 2021: 16700-16713 - [i9]Xinwei Yu, Matthew S. Creamer, Francesco Randi, Anuj K. Sharma, Scott W. Linderman, Andrew M. Leifer:
Fast deep learning correspondence for neuron tracking and identification in C.elegans using synthetic training. CoRR abs/2101.08211 (2021) - [i8]Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman:
Generalized Shape Metrics on Neural Representations. CoRR abs/2110.14739 (2021) - [i7]Jimmy T. H. Smith, Scott W. Linderman, David Sussillo:
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. CoRR abs/2111.01256 (2021) - 2020
- [c21]David M. Zoltowski, Jonathan W. Pillow, Scott W. Linderman:
A general recurrent state space framework for modeling neural dynamics during decision-making. ICML 2020: 11680-11691 - [c20]Joshua I. Glaser, Matthew R. Whiteway, John P. Cunningham, Liam Paninski, Scott W. Linderman:
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations. NeurIPS 2020 - [c19]Alex H. Williams, Anthony Degleris, Yixin Wang, Scott W. Linderman:
Point process models for sequence detection in high-dimensional neural spike trains. NeurIPS 2020 - [i6]Alex H. Williams, Anthony Degleris, Yixin Wang, Scott W. Linderman:
Point process models for sequence detection in high-dimensional neural spike trains. CoRR abs/2010.04875 (2020) - [i5]Arunesh Mittal, Scott W. Linderman, John W. Paisley, Paul Sajda:
Bayesian recurrent state space model for rs-fMRI. CoRR abs/2011.07365 (2020)
2010 – 2019
- 2019
- [c18]Josue Nassar, Scott W. Linderman, Mónica F. Bugallo, Il Memming Park:
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling. ICLR (Poster) 2019 - [c17]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. NeurIPS 2019: 781-792 - [c16]Ifigeneia Apostolopoulou, Scott W. Linderman, Kyle Miller, Artur Dubrawski:
Mutually Regressive Point Processes. NeurIPS 2019: 5116-5127 - [c15]Ruoxi Sun, Scott W. Linderman, Ian Kinsella, Liam Paninski:
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models. NeurIPS 2019: 10165-10174 - [c14]Eleanor Batty, Matthew R. Whiteway, Shreya Saxena, Dan Biderman, Taiga Abe, Simon Musall, Winthrop Gillis, Jeffrey E. Markowitz, Anne Churchland, John P. Cunningham, Sandeep R. Datta, Scott W. Linderman, Liam Paninski:
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos. NeurIPS 2019: 15680-15691 - [i4]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. CoRR abs/1910.12991 (2019) - 2018
- [c13]Josue Nassar, Scott W. Linderman, Yuan Zhao, Mónica F. Bugallo, Il Memming Park:
Learning Structured Neural Dynamics From Single Trial Population Recording. ACSSC 2018: 666-670 - [c12]Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei:
Variational Sequential Monte Carlo. AISTATS 2018: 968-977 - [c11]Scott W. Linderman, Gonzalo E. Mena, Hal James Cooper, Liam Paninski, John P. Cunningham:
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference. AISTATS 2018: 1618-1627 - [c10]Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek:
Learning Latent Permutations with Gumbel-Sinkhorn Networks. ICLR (Poster) 2018 - [c9]Anuj Sharma, Robert Johnson, Florian Engert, Scott W. Linderman:
Point process latent variable models of larval zebrafish behavior. NeurIPS 2018: 10942-10953 - [i3]Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek:
Learning Latent Permutations with Gumbel-Sinkhorn Networks. CoRR abs/1802.08665 (2018) - [i2]Josue Nassar, Scott W. Linderman, Mónica F. Bugallo, Il Memming Park:
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling. CoRR abs/1811.12386 (2018) - 2017
- [c8]Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei:
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. AISTATS 2017: 489-498 - [c7]Scott W. Linderman, Matthew J. Johnson, Andrew C. Miller, Ryan P. Adams, David M. Blei, Liam Paninski:
Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems. AISTATS 2017: 914-922 - [c6]Scott W. Linderman, Matthew J. Johnson:
Structure-Exploiting variational inference for recurrent switching linear dynamical systems. CAMSAP 2017: 1-5 - 2016
- [j1]Huseyin Melih Elibol, Vincent Nguyen, Scott W. Linderman, Matthew J. Johnson, Amna Hashmi, Finale Doshi-Velez:
Cross-Corpora Unsupervised Learning of Trajectories in Autism Spectrum Disorders. J. Mach. Learn. Res. 17: 133:1-133:38 (2016) - [c5]Zhe Chen, Scott W. Linderman, Matthew A. Wilson:
Bayesian nonparametric methods for discovering latent structures of rat hippocampal ensemble spikes. MLSP 2016: 1-6 - [c4]Scott W. Linderman, Ryan P. Adams, Jonathan W. Pillow:
Bayesian latent structure discovery from multi-neuron recordings. NIPS 2016: 2002-2010 - 2015
- [c3]Scott W. Linderman, Matthew J. Johnson, Ryan P. Adams:
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation. NIPS 2015: 3456-3464 - 2014
- [c2]Scott W. Linderman, Ryan P. Adams:
Discovering Latent Network Structure in Point Process Data. ICML 2014: 1413-1421 - [c1]Scott W. Linderman, Christopher H. Stock, Ryan P. Adams:
A framework for studying synaptic plasticity with neural spike train data. NIPS 2014: 2330-2338 - [i1]Scott W. Linderman, Ryan P. Adams:
Discovering Latent Network Structure in Point Process Data. CoRR abs/1402.0914 (2014)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:19 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
