Point process models for sequence detection in high-dimensional neural spike trains

10 October 2020

Papers citing "Point process models for sequence detection in high-dimensional neural spike trains"

8 / 8 papers shown

Title
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes Zhiheng Chen Guanhua Fang Wen Yu 70 0 0 02 Jun 2024
Understanding Activation Patterns in Artificial Neural Networks by Exploring Stochastic Processes S. Lehmler Muhammad Saif-ur-Rehman Tobias Glasmachers Ioannis Iossifidis 65 0 0 01 Aug 2023
EasyTPP: Towards Open Benchmarking Temporal Point Processes Siqiao Xue Xiaoming Shi Zhixuan Chu Yan Wang Hongyan Hao ... Chenyuan Pan James Y. Zhang Qingsong Wen Junqing Zhou Hongyuan Mei AI4TS 104 32 0 16 Jul 2023
Anticipatory Music Transformer John Thickstun David Leo Wright Hall Chris Donahue Percy Liang 64 16 0 14 Jun 2023
Conditional Generative Modeling for High-dimensional Marked Temporal Point Processes Zheng Dong Zekai Fan Shixiang Zhu DiffM 112 4 0 21 May 2023
Variational Inference for Neyman-Scott Processes Chengkuan Hong C. Shelton BDL 52 2 0 07 Mar 2023
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models Yixin Wang Anthony Degleris Alex H. Williams Scott W. Linderman 57 4 0 13 Jan 2022
Deep Neyman-Scott Processes Chengkuan Hong C. Shelton 119 5 0 06 Nov 2021