Deep Random Splines for Point Process Intensity Estimation of Neural
Population Data

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Deep Random Splines for Point Process Intensity Estimation of Neural Population Data

6 March 2019

Gabriel Loaiza-Ganem

Sean M. Perkins

Karen E. Schroeder

Mark M. Churchland

John P. Cunningham

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Papers citing "Deep Random Splines for Point Process Intensity Estimation of Neural Population Data"

11 / 11 papers shown

Title
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 524 10,591 0 17 Feb 2020
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 92 665 0 28 Oct 2019
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions Robert Tibshirani 96 43 0 12 May 2017
OptNet: Differentiable Optimization as a Layer in Neural Networks Brandon Amos J. Zico Kolter 171 972 0 01 Mar 2017
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 202 417 0 11 Oct 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 433 18,361 0 27 May 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 72 155 0 26 May 2016
Composing graphical models with neural networks for structured representations and fast inference Matthew J. Johnson David Duvenaud Alexander B. Wiltschko S. R. Datta Ryan P. Adams BDL OCL 92 485 0 20 Mar 2016
Variational Inference for Gaussian Process Modulated Poisson Processes C. Lloyd Tom Gunter Michael A. Osborne Stephen J. Roberts 77 117 0 02 Nov 2014
Adaptive Bayesian density regression for high-dimensional data Weining Shen S. Ghosal 95 26 0 11 Mar 2014
Scaling Multidimensional Inference for Structured Gaussian Processes Elad Gilboa Yunus Saatci John P. Cunningham 121 61 0 18 Sep 2012