stochastic differential equation

Efficient and Flexible Inference for Stochastic Systems NeurIPS 2017 Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo ICML 2017 Linking Micro Event History to Macro Prediction in Point Process Models AISTATS 2017 Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms ICML 2017 A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes JMLR 2016 Hawkes Processes with Stochastic Excitations ICML 2016 Learning and Forecasting Opinion Dynamics in Social Networks NeurIPS 2016 Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes NeurIPS 2016 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012 The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes NeurIPS 2012 A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration NeurIPS 2010 Approximate inference in continuous time Gaussian-Jump processes NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Why are DBNs sparse? AISTATS 2010 Continuous Time Particle Filtering for fMRI NeurIPS 2007