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Poisson intensity estimation with reproducing kernels

27 October 2016

Seth Flaxman

Yee Whye Teh

Dino Sejdinovic

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Papers citing "Poisson intensity estimation with reproducing kernels"

21 / 21 papers shown

Title
K $^2$ IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes Hideaki Kim Tomoharu Iwata Akinori Fujino 20 0 0 30 May 2025
Squared families: Searching beyond regular probability models Russell Tsuchida Jiawei Liu Cheng Soon Ong Dino Sejdinovic 68 0 0 27 Mar 2025
Nonparametric estimation of Hawkes processes with RKHSs Anna Bonnet Maxime Sangnier 99 0 0 01 Nov 2024
Nonstationary Sparse Spectral Permanental Process Zicheng Sun Yixuan Zhang Zenan Ling Xuhui Fan Feng Zhou 36 0 0 04 Oct 2024
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families Russell Tsuchida Cheng Soon Ong Dino Sejdinovic 57 5 0 14 Feb 2024
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data Yongsheng Mei Mahdi Imani Tian-Shing Lan GP 80 5 0 25 Jan 2024
Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization Xu Cai Jonathan Scarlett 58 0 0 11 Jan 2024
Squared Neural Families: A New Class of Tractable Density Models Russell Tsuchida Cheng Soon Ong Dino Sejdinovic TPM 63 12 0 22 May 2023
Sensing Cox Processes via Posterior Sampling and Positive Bases Mojmír Mutný Andreas Krause 44 5 0 21 Oct 2021
Spatio-temporal extreme event modeling of terror insurgencies Lekha Patel L. Shand J. D. Tucker G. Huerta 19 3 0 15 Oct 2021
Sparse Representations of Positive Functions via First and Second-Order Pseudo-Mirror Descent A. Chakraborty K. Rajawat Alec Koppel 44 3 0 13 Nov 2020
Additive Poisson Process: Learning Intensity of Higher-Order Interaction in Stochastic Processes S. Luo Feng Zhou Lamiae Azizi M. Sugiyama 132 0 0 16 Jun 2020
All your loss are belong to Bayes Christian J. Walder Richard Nock 61 5 0 08 Jun 2020
Hard Shape-Constrained Kernel Machines Pierre-Cyril Aubin-Frankowski Z. Szabó 62 22 0 26 May 2020
Quantile Propagation for Wasserstein-Approximate Gaussian Processes Rui Zhang Christian J. Walder Edwin V. Bonilla Marian-Andrei Rizoiu Lexing Xie 8 2 0 21 Dec 2019
Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns Raif M. Rustamov James T. Klosowski 39 7 0 31 May 2019
Efficient EM-Variational Inference for Hawkes Process Feng Zhou Zhidong Li Xuhui Fan Yang Wang Arcot Sowmya Fang Chen 30 8 0 29 May 2019
Efficient Non-parametric Bayesian Hawkes Processes Rui Zhang Christian J. Walder Marian-Andrei Rizoiu Lexing Xie 74 38 0 08 Oct 2018
Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes Christian Donner Manfred Opper 84 36 0 02 Aug 2018
Large-Scale Cox Process Inference using Variational Fourier Features S. T. John J. Hensman 57 31 0 03 Apr 2018
Nonparametric Hawkes Processes: Online Estimation and Generalization Bounds Yingxiang Yang Jalal Etesami Niao He Negar Kiyavash 70 5 0 25 Jan 2018