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Variational Inference for Gaussian Process Modulated Poisson Processes

2 November 2014

Papers citing "Variational Inference for Gaussian Process Modulated Poisson Processes"

34 / 34 papers shown

Title
K $^2$ IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes Hideaki Kim Tomoharu Iwata Akinori Fujino 18 0 0 30 May 2025
Nonparametric estimation of Hawkes processes with RKHSs Anna Bonnet Maxime Sangnier 99 0 0 01 Nov 2024
Causal Modeling of Policy Interventions From Sequences of Treatments and Outcomes Caglar Hizli S. T. John A. Juuti Tuure Saarinen Kirsi Pietiläinen Pekka Marttinen CML 59 1 0 09 Sep 2022
Survival Analysis of the Compressor Station Based on Hawkes Process with Weibull Base Intensity Lu-ning Zhang Jian Liu Xin Zuo 50 0 0 27 Dec 2021
Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach Minyoung Kim Vladimir Pavlovic BDL 91 6 0 05 Feb 2021
Multi-output Gaussian Process Modulated Poisson Processes for Event Prediction Salman Jahani Shiyu Zhou D. Veeramani Jeff Schmidt 58 11 0 06 Nov 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 45 25 0 07 Oct 2020
Graph Convolutional Networks Reveal Neural Connections Encoding Prosthetic Sensation Vivek Subramanian Joshua Khani 20 0 0 23 Aug 2020
Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport T. L. J. Ng A. Zammit‐Mangion 36 6 0 01 Jul 2020
All your loss are belong to Bayes Christian J. Walder Richard Nock 61 5 0 08 Jun 2020
BART-based inference for Poisson processes Stamatina Lamprinakou Mauricio Barahona Seth Flaxman Sarah Filippi Axel Gandy E. McCoy 37 6 0 16 May 2020
Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation Feng Zhou Zhidong Li Xuhui Fan Yang Wang Arcot Sowmya Fang Chen 53 2 0 29 Oct 2019
Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data James A. Grant David S. Leslie 49 1 0 20 Jun 2019
Efficient EM-Variational Inference for Hawkes Process Feng Zhou Zhidong Li Xuhui Fan Yang Wang Arcot Sowmya Fang Chen 28 8 0 29 May 2019
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes Xubo Yue Raed Al Kontar 85 17 0 09 Mar 2019
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data Gabriel Loaiza-Ganem Sean M. Perkins Karen E. Schroeder Mark M. Churchland John P. Cunningham 3DPC 76 14 0 06 Mar 2019
Gaussian Process Modulated Cox Processes under Linear Inequality Constraints A. F. López-Lopera S. T. John N. Durrande 72 16 0 28 Feb 2019
Functional Regularisation for Continual Learning with Gaussian Processes Michalis K. Titsias Jonathan Richard Schwarz A. G. Matthews Razvan Pascanu Yee Whye Teh CLL BDL 71 187 0 31 Jan 2019
GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language Jamie Fairbrother Christopher Nemeth M. Rischard Johanni Brea Thomas Pinder GP VLM 67 24 0 21 Dec 2018
Efficient Non-parametric Bayesian Hawkes Processes Rui Zhang Christian J. Walder Marian-Andrei Rizoiu Lexing Xie 61 38 0 08 Oct 2018
Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes Christian Donner Manfred Opper 82 36 0 02 Aug 2018
Efficient Inference in Multi-task Cox Process Models Virginia Aglietti Theodoros Damoulas Edwin V. Bonilla 58 8 0 24 May 2018
Variational Learning on Aggregate Outputs with Gaussian Processes H. Law Dino Sejdinovic E. Cameron T. Lucas Seth Flaxman K. Battle Kenji Fukumizu 48 38 0 22 May 2018
Large-Scale Cox Process Inference using Variational Fourier Features S. T. John J. Hensman 57 31 0 03 Apr 2018
Decoupled Learning for Factorial Marked Temporal Point Processes Weichang Wu Junchi Yan Xiaokang Yang H. Zha 40 20 0 21 Jan 2018
Scalable high-resolution forecasting of sparse spatiotemporal events with kernel methods: a winning solution to the NIJ "Real-Time Crime Forecasting Challenge" Seth Flaxman Michael Chirico Pau Pereira Charles E. Loeffler 62 50 0 09 Jan 2018
Bayesian Computation for Log-Gaussian Cox Processes--A Comparative Analysis of Methods Ming Teng F. Nathoo T. Johnson 57 38 0 03 Jan 2017
Variational Fourier features for Gaussian processes J. Hensman N. Durrande Arno Solin VLM 87 202 0 21 Nov 2016
Poisson intensity estimation with reproducing kernels Seth Flaxman Yee Whye Teh Dino Sejdinovic 89 48 0 27 Oct 2016
Patient Flow Prediction via Discriminative Learning of Mutually-Correcting Processes Hongteng Xu Weichang Wu S. Nemati H. Zha AI4TS OOD 38 46 0 14 Feb 2016
Learning Granger Causality for Hawkes Processes Hongteng Xu Mehrdad Farajtabar H. Zha AI4TS CML 71 227 0 14 Feb 2016
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes T. Nickson Tom Gunter C. Lloyd Michael A. Osborne Stephen J. Roberts 78 21 0 27 Oct 2015
MCMC for Variationally Sparse Gaussian Processes J. Hensman A. G. Matthews Maurizio Filippone Zoubin Ghahramani 83 141 0 12 Jun 2015
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes A. G. Matthews J. Hensman Richard Turner Zoubin Ghahramani 108 192 0 27 Apr 2015