point process

DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals ICLR 2022 Efficient Inference for Dynamic Flexible Interactions of Neural Populations JMLR 2022 Explaining Point Processes by Learning Interpretable Temporal Logic Rules ICLR 2022 Fast Bayesian Estimation of Point Process Intensity as Function of Covariates NeurIPS 2022 Interval-censored Hawkes processes JMLR 2022 Linking Transformer to Hawkes Process for Information Cascade Prediction (Student Abstract) AAAI 2022 Multiclass classification for Hawkes processes UAI 2022 Neural Network Poisson Models for Behavioural and Neural Spike Train Data ICML 2022 Online Neural Sequence Detection with Hierarchical Dirichlet Point Process NeurIPS 2022 Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process IJCAI 2022 A Differentiable Point Process with Its Application to Spiking Neural Networks ICML 2021 Cardinality-Regularized Hawkes-Granger Model NeurIPS 2021 Continuous-time edge modelling using non-parametric point processes NeurIPS 2021 Dynamic Analysis of Higher-Order Coordination in Neuronal Assemblies via De-Sparsified Orthogonal Matching Pursuit NeurIPS 2021 Event Outlier Detection in Continuous Time ICML 2021 Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation NeurIPS 2021 Relaxed Clustered Hawkes Process for Student Procrastination Modeling in MOOCs AAAI 2021 Row-clustering of a Point Process-valued Matrix NeurIPS 2021 Scalable Normalizing Flows for Permutation Invariant Densities ICML 2021 Self-Adaptable Point Processes with Nonparametric Time Decays NeurIPS 2021 The diffusion of scientific terms – tracing individuals’ influence in the history of science for English EMNLP 2021 UNIPoint: Universally Approximating Point Processes Intensities AAAI 2021 A Model of Fake Data in Data-driven Analysis JMLR 2020 A Variational Point Process Model for Social Event Sequences AAAI 2020 Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes AISTATS 2020