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Noise-Contrastive Estimation for Multivariate Point Processes

Noise-Contrastive Estimation for Multivariate Point Processes

Neural Information Processing Systems (NeurIPS), 2020
2 November 2020
Hongyuan Mei
Tom Wan
Jason Eisner
ArXiv (abs)PDFHTML

Papers citing "Noise-Contrastive Estimation for Multivariate Point Processes"

17 / 17 papers shown
Addressing Mark Imbalance in Integration-free Neural Marked Temporal Point Processes
Addressing Mark Imbalance in Integration-free Neural Marked Temporal Point Processes
Sishun Liu
Ke Deng
Xiuzhen Zhang
Yongli Ren
Yan Wang
AI4TS
210
0
0
23 Oct 2025
Self-Supervised Contrastive Pre-Training for Multivariate Point
  Processes
Self-Supervised Contrastive Pre-Training for Multivariate Point Processes
Xiao Shou
D. Subramanian
D. Bhattacharjya
Tian Gao
Kristin P. Bennet
3DPCSSL
228
2
0
01 Feb 2024
Distribution-Free Conformal Joint Prediction Regions for Neural Marked
  Temporal Point Processes
Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point ProcessesMachine-mediated learning (ML), 2024
Victor Dheur
T. Bosser
Rafael Izbicki
Souhaib Ben Taieb
AI4TS
478
8
0
09 Jan 2024
Non-Autoregressive Diffusion-based Temporal Point Processes for
  Continuous-Time Long-Term Event Prediction
Non-Autoregressive Diffusion-based Temporal Point Processes for Continuous-Time Long-Term Event Prediction
Wang-Tao Zhou
Zhao Kang
Ling Tian
DiffM
293
7
0
02 Nov 2023
SMURF-THP: Score Matching-based UnceRtainty quantiFication for
  Transformer Hawkes Process
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes ProcessInternational Conference on Machine Learning (ICML), 2023
Zichong Li
Yanbo Xu
Simiao Zuo
Hao Jiang
Chao Zhang
Tuo Zhao
H. Zha
252
8
0
25 Oct 2023
Score Matching-based Pseudolikelihood Estimation of Neural Marked
  Spatio-Temporal Point Process with Uncertainty Quantification
Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification
Zichong Li
Qunzhi Xu
Zhenghao Xu
Yajun Mei
Tuo Zhao
Hongyuan Zha
252
1
0
25 Oct 2023
Intensity-free Integral-based Learning of Marked Temporal Point
  Processes
Intensity-free Integral-based Learning of Marked Temporal Point Processes
Sishun Liu
Ke Deng
Xiuzhen Zhang
Yongli Ren
329
0
0
04 Aug 2023
On the Predictive Accuracy of Neural Temporal Point Process Models for
  Continuous-time Event Data
On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data
T. Bosser
Souhaib Ben Taieb
AI4TS
233
13
0
29 Jun 2023
Spatio-temporal Diffusion Point Processes
Spatio-temporal Diffusion Point ProcessesKnowledge Discovery and Data Mining (KDD), 2023
Yuan Yuan
Jingtao Ding
Chenyang Shao
Depeng Jin
Yong Li
DiffM
383
77
0
21 May 2023
Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal
  Point Processes
Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal Point ProcessesInternational Conference on Information and Knowledge Management (CIKM), 2022
Govind V Waghmare
Ankur Debnath
Siddhartha Asthana
Aakarsh Malhotra
224
8
0
27 Oct 2022
FaDIn: Fast Discretized Inference for Hawkes Processes with General
  Parametric Kernels
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric KernelsInternational Conference on Machine Learning (ICML), 2022
Guillaume Staerman
Cédric Allain
Alexandre Gramfort
Thomas Moreau
535
7
0
10 Oct 2022
HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon
  Prediction of Event Sequences
HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event SequencesNeural Information Processing Systems (NeurIPS), 2022
Siqiao Xue
Xiaoming Shi
James Y. Zhang
Hongyuan Mei
AI4TS
239
55
0
04 Oct 2022
Exploring Generative Neural Temporal Point Process
Exploring Generative Neural Temporal Point Process
Haitao Lin
Lirong Wu
Guojiang Zhao
Pai Liu
Stan Z. Li
DiffM
362
33
0
03 Aug 2022
Transformer Embeddings of Irregularly Spaced Events and Their
  Participants
Transformer Embeddings of Irregularly Spaced Events and Their ParticipantsInternational Conference on Learning Representations (ICLR), 2021
Chenghao Yang
Hongyuan Mei
Jason Eisner
AI4TS
472
60
0
31 Dec 2021
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG
  Signals
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals
Cédric Allain
Alexandre Gramfort
Thomas Moreau
195
5
0
08 Dec 2021
An Empirical Study: Extensive Deep Temporal Point Process
An Empirical Study: Extensive Deep Temporal Point Process
Haitao Lin
Cheng Tan
Lirong Wu
Zhangyang Gao
Stan. Z. Li
AI4TS
386
14
0
19 Oct 2021
Hawkes Processes on Graphons
Hawkes Processes on Graphons
Hongteng Xu
Dixin Luo
H. Zha
203
1
0
04 Feb 2021
1
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