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. 2006.10968
  4. Cited By
The Normal-Generalised Gamma-Pareto process: A novel pure-jump Lévy
  process with flexible tail and jump-activity properties

The Normal-Generalised Gamma-Pareto process: A novel pure-jump Lévy process with flexible tail and jump-activity properties

19 June 2020
Fadhel Ayed
Juho Lee
François Caron
ArXivPDFHTML

Papers citing "The Normal-Generalised Gamma-Pareto process: A novel pure-jump Lévy process with flexible tail and jump-activity properties"

3 / 3 papers shown
Title
Deep neural networks with dependent weights: Gaussian Process mixture
  limit, heavy tails, sparsity and compressibility
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility
Hoileong Lee
Fadhel Ayed
Paul Jung
Juho Lee
Hongseok Yang
François Caron
48
10
0
17 May 2022
On sparsity, power-law and clustering properties of graphex processes
On sparsity, power-law and clustering properties of graphex processes
François Caron
F. Panero
Judith Rousseau
31
11
0
10 Aug 2017
Modeling high-frequency financial data by pure jump processes
Modeling high-frequency financial data by pure jump processes
Bing-Yi Jing
Xinbing Kong
Zhi Liu
41
65
0
05 Jun 2012
1