ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1411.0254
  4. Cited By
Variational Inference for Gaussian Process Modulated Poisson Processes

Variational Inference for Gaussian Process Modulated Poisson Processes

2 November 2014
C. Lloyd
Tom Gunter
Michael A. Osborne
Stephen J. Roberts
ArXivPDFHTML

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

14 / 14 papers shown
Title
Nonparametric estimation of Hawkes processes with RKHSs
Nonparametric estimation of Hawkes processes with RKHSs
Anna Bonnet
Maxime Sangnier
39
0
0
01 Nov 2024
Modelling financial volume curves with hierarchical Poisson processes
Modelling financial volume curves with hierarchical Poisson processes
Creighton Heaukulani
Abhinav Pandey
Lancelot F. James
30
1
0
01 Jun 2024
Heterogeneous Multi-Task Gaussian Cox Processes
Heterogeneous Multi-Task Gaussian Cox Processes
Feng Zhou
Quyu Kong
Zhijie Deng
Fengxiang He
Peng Cui
Jun Zhu
38
2
0
29 Aug 2023
Multi-output Gaussian Process Modulated Poisson Processes for Event
  Prediction
Multi-output Gaussian Process Modulated Poisson Processes for Event Prediction
Salman Jahani
Shiyu Zhou
D. Veeramani
Jeff Schmidt
10
11
0
06 Nov 2020
All your loss are belong to Bayes
All your loss are belong to Bayes
Christian J. Walder
Richard Nock
16
5
0
08 Jun 2020
Posterior Contraction Rates for Gaussian Cox Processes with
  Non-identically Distributed Data
Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data
James A. Grant
David S. Leslie
21
1
0
20 Jun 2019
Variational Inference of Joint Models using Multivariate Gaussian
  Convolution Processes
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes
Xubo Yue
Raed Al Kontar
32
16
0
09 Mar 2019
Gaussian Process Modulated Cox Processes under Linear Inequality
  Constraints
Gaussian Process Modulated Cox Processes under Linear Inequality Constraints
A. F. López-Lopera
S. T. John
N. Durrande
18
16
0
28 Feb 2019
GaussianProcesses.jl: A Nonparametric Bayes package for the Julia
  Language
GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language
Jamie Fairbrother
Christopher Nemeth
M. Rischard
Johanni Brea
Thomas Pinder
GP
VLM
27
24
0
21 Dec 2018
Efficient Non-parametric Bayesian Hawkes Processes
Efficient Non-parametric Bayesian Hawkes Processes
Rui Zhang
Christian J. Walder
Marian-Andrei Rizoiu
Lexing Xie
19
37
0
08 Oct 2018
Decoupled Learning for Factorial Marked Temporal Point Processes
Decoupled Learning for Factorial Marked Temporal Point Processes
Weichang Wu
Junchi Yan
Xiaokang Yang
H. Zha
23
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"
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
13
50
0
09 Jan 2018
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes
T. Nickson
Tom Gunter
C. Lloyd
Michael A. Osborne
Stephen J. Roberts
19
21
0
27 Oct 2015
On Sparse variational methods and the Kullback-Leibler divergence
  between stochastic processes
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes
A. G. Matthews
J. Hensman
Richard Turner
Zoubin Ghahramani
39
189
0
27 Apr 2015
1