Andreas Lindholm
Gästforskare vid Institutionen för medicinska vetenskaper; Klinisk epidemiologi
- E-post:
- andreas.lindholm@uu.se
- Besöksadress:
- Akademiska sjukhuset, ingång 40, 5 tr
751 85 UPPSALA - Postadress:
- Akademiska sjukhuset, ingång 40, 5 tr
751 85 UPPSALA
- ORCID:
- 0000-0002-5601-1687
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Publikationer
Senaste publikationer
- Predicting Political Violence Using a State-Space Model (2022)
- Data Consistency Approach to Model Validation (2019)
- Identification of a Duffing oscillator using particle Gibbs with ancestor sampling (2019)
- Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo (2018)
- Machine learning with state-space models, Gaussian processes and Monte Carlo methods (2018)
Alla publikationer
Artiklar
- Predicting Political Violence Using a State-Space Model (2022)
- Data Consistency Approach to Model Validation (2019)
- Identification of a Duffing oscillator using particle Gibbs with ancestor sampling (2019)
- Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo (2018)
- Learning of state-space models with highly informative observations (2018)
- Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes (2018)
- A flexible state–space model for learning nonlinear dynamical systems (2017)
- Learning dynamical systems with particle stochastic approximation EM
Böcker
- Machine learning with state-space models, Gaussian processes and Monte Carlo methods (2018)
- Learning probabilistic models of dynamical phenomena using particle filters (2016)
Konferenser
- Learning nonlinear state-space models using smooth particle-filter-based likelihood approximations (2018)
- How consistent is my model with the data? (2018)
- Computationally Efficient Bayesian Learning of Gaussian Process State Space Models (2016)
- Marginalizing Gaussian process hyperparameters using sequential Monte Carlo (2015)
- Nonlinear state space smoothing using the conditional particle filter (2015)
- Nonlinear state space model identification using a regularized basis function expansion (2015)
- Identification of jump Markov linear models using particle filters (2014)