| Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era | Feb 26, 2019 | Gaussian ProcessesState Space Models | —Unverified | 0 |
| A dynamic factor model approach to incorporate Big Data in state space models for official statistics | Jan 31, 2019 | State Space Models | CodeCode Available | 0 |
| Stochastic Gradient MCMC for Nonlinear State Space Models | Jan 29, 2019 | Bayesian InferenceState Space Models | CodeCode Available | 0 |
| Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction | Jan 23, 2019 | State Space ModelsTime Series | CodeCode Available | 0 |
| Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler | Jan 3, 2019 | Gaussian ProcessesState Space Models | —Unverified | 0 |
| Closed-form Inference and Prediction in Gaussian Process State-Space Models | Dec 10, 2018 | FormState Space Models | —Unverified | 0 |
| Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation | Dec 1, 2018 | Bayesian InferenceComputational Efficiency | —Unverified | 0 |
| Explainable Genetic Inheritance Pattern Prediction | Dec 1, 2018 | Causal InferencePrediction | —Unverified | 0 |
| Deep State Space Models for Time Series Forecasting | Dec 1, 2018 | Deep LearningProbabilistic Time Series Forecasting | —Unverified | 0 |
| Black-Box Autoregressive Density Estimation for State-Space Models | Nov 20, 2018 | Bayesian InferenceDeep Learning | —Unverified | 0 |
