arXiv:2210.15549
공식 코드 · Papers with Code
Closed-form modeling of neuronal spike train statistics using multivariate Hawkes cumulants
원문 초록
We derive exact analytical expressions for the cumulants of any orders of neuronal membrane potentials driven by spike trains in a multivariate Hawkes process model with excitation and inhibition. Such expressions can be used for the prediction and sensitivity analysis of the statistical behavior of the model over time, and to estimate the probability densities of neuronal membrane potentials using Gram-Charlier expansions. Our results are shown to provide a better alternative to Monte Carlo estimates via stochastic simulations, and computer codes based on combinatorial recursions are included.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Generative Latent Kernel Modeling for Blind Motion Deblurring
Differentially Private Relational Learning with Entity-level Privacy Guarantees
EtiCor++: Towards Understanding Etiquettical Bias in LLMs
Fragility in Average Treatment Effect on the Treated under Limited Covariate Support
Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning
Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.