Matthew T. Kaufman

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All published works

Action	Title	Year	Authors
+ PDF Chat	Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time	2021	Zhu Feng Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci Chethan Pandarinath
+	Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity	2021	Felix Pei Joel Ye David L. Zoltowski Anqi Wu Raeed H. Chowdhury Hansem Sohn Joseph E. O’Doherty Krishna V. Shenoy Matthew T. Kaufman Mark M. Churchland
+	Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time	2021	Zhu Feng Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci Chethan Pandarinath

Common Coauthors

Coauthor	Papers Together
Chethan Pandarinath	3
Andrea Giovannucci	2
Andrew R. Sedler	2
Harrison A. Grier	2
Nauman Ahad	2
Mark A. Davenport	2
Zhu Feng	2
Eva L. Dyer	1
Hansem Sohn	1
Joseph E. O’Doherty	1
Mehrdad Jazayeri	1
Raeed H. Chowdhury	1
Felix Pei	1
Krishna V. Shenoy	1
Mark M. Churchland	1
David L. Zoltowski	1
Joel Ye	1
Anqi Wu	1
Jonathan W. Pillow	1
Il Memming Park	1
Lee E. Miller	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Enabling hyperparameter optimization in sequential autoencoders for spiking neural data	2019	Mohammad Reza Keshtkaran Chethan Pandarinath	2
+ PDF Chat	Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains	2017	Yuan Zhao Il Memming Park	2
+	Linear dynamical neural population models through nonlinear embeddings	2016	Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham	2
+	Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks	2019	Qi She Anqi Wu	2
+	An Overview of Low-Rank Matrix Recovery From Incomplete Observations	2016	Mark A. Davenport Justin Romberg	1
+	LFADS - Latent Factor Analysis via Dynamical Systems	2016	David Sussillo Rafał Józefowicz L. F. Abbott Chethan Pandarinath	1
+ PDF Chat	Fast online deconvolution of calcium imaging data	2017	Johannes Friedrich Pengcheng Zhou Liam Paninski	1
+	Simultaneous recovery of a series of low-rank matrices by locally weighted matrix smoothing	2017	Liangbei Xu Mark A. Davenport	1
+	Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling	2018	Josue Nassar Scott W. Linderman Mónica F. Bugallo Il Memming Park	1
+	EvalAI: Towards Better Evaluation Systems for AI Agents	2019	Deshraj Jain Rishabh Jain Harsh Agrawal Prithvijit Chattopadhyay Taranjeet Singh Akash Jain Shivkaran Singh Stefan Lee Dhruv Batra	1
+	Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification	2018	Max Simchowitz Horia Mania Stephen Tu Michael I. Jordan Benjamin Recht	1
+	Gradient Descent Learns Linear Dynamical Systems	2018	Moritz Hardt Tengyu Ma Benjamin Recht	1
+	Spectral Filtering for General Linear Dynamical Systems	2018	Elad Hazan Holden Lee Karan Singh Cyril Zhang Yi Zhang	1
+ PDF Chat	Non-asymptotic Identification of LTI Systems from a Single Trajectory	2019	Samet Oymak Necmiye Özay	1
+ PDF Chat	Pyglmnet: Python implementation of elastic-net regularized generalized linear models	2020	Mainak Jas Titipat Achakulvisut Aid Idrizović Daniel E. Acuña Matthew Antalek Vinícius Abrão da Silva Marques Tommy Odland Ravi Garg Mayank Agrawal Yu Umegaki	1
+ PDF Chat	Finite Sample Analysis of Stochastic System Identification	2019	Anastasios Tsiamis George J. Pappas	1
+	Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis	2020	Ming Bo Cai Michael Shvartsman Anqi Wu Hejia Zhang Xia Zhu	1
+	Dynamic Knowledge embedding and tracing	2020	Liangbei Xu Mark A. Davenport	1
+	Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations	2019	Stephen Keeley David M. Zoltowski Jonathan W. Pillow Spencer L. Smith Yiyi Yu	1
+ PDF Chat	Variational Online Learning of Neural Dynamics	2020	Yuan Zhao Il Memming Park	1
+	Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE	2020	Ding Zhou Xue-Xin Wei	1
+ PDF Chat	A zero-inflated gamma model for post-deconvolved calcium imaging traces	2019	Xue-Xin Wei Ding Zhou Andres Grosmark Zaki Ajabi Fraser T. Sparks Pengcheng Zhou Mark P. Brandon Attila Losonczy Liam Paninski	1
+	Manifold GPLVMs for discovering non-Euclidean latent structure in neural data	2020	Kristopher T. Jensen Ta-Chu Kao Marco Tripodi Guillaume Hennequin	1
+	Representation learning for neural population activity with Neural Data Transformers	2021	Joel Ye Chethan Pandarinath	1
+ PDF Chat	Building population models for large-scale neural recordings: Opportunities and pitfalls	2021	Cole Hurwitz Nina Kudryashova Arno Onken Matthias H. Hennig	1
+	Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time	2021	Zhu Feng Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci Chethan Pandarinath	1
+	Targeted Neural Dynamical Modeling	2021	Cole Hurwitz Akash Srivastava Kai Xu Justin Jude Matthew G. Perich Lee E. Miller Matthias H. Hennig	1
+ PDF Chat	On simplicity and complexity in the brave new world of large-scale neuroscience	2015	Peiran Gao Surya Ganguli	1
+ PDF Chat	Unsupervised Visual Representation Learning by Context Prediction	2015	Carl Doersch Abhinav Gupta Alexei A. Efros	1
+ PDF Chat	Approximate Methods for State-Space Models	2010	Shinsuke Koyama Lucia Castellanos Pérez-Bolde Cosma Rohilla Shalizi Robert E. Kass	1
+ PDF Chat	Representation Learning: A Review and New Perspectives	2013	Yoshua Bengio Aaron Courville P. M. Durai Raj Vincent	1
+	Session-based Recommendations with Recurrent Neural Networks	2015	Balázs Hidasi Alexandros Karatzoglou Linas Baltrunas Domonkos Tikk	1