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Milan Papež

  1. Papež Milan, Quinn Anthony :  Transferring model structure in Bayesian transfer learning for Gaussian process regression , Knowledge-Based System vol.251, 108875 [2022] Download Download DOI: 10.1016/j.knosys.2022.108875
  2. Papež Milan, Quinn Anthony :  Bayesian transfer learning between Student-t filters , Signal Processing, 107624 [2020] Download Download DOI: 10.1016/j.sigpro.2020.107624

  1. Papež Milan, Quinn Anthony :  Hierarchical Bayesian Transfer Learning Between a Pair of Kalman Filters , Proceedings of the 32nd Irish Signals and Systems Conference (ISSC) 2021, 9467863 , Irish Signals and Systems Conference (ISSC 2021) /23./, (Athlone, IE, 20210610) [2021] Download DOI: 10.1109/ISSC52156.2021.9467863
  2. Papež Milan, Quinn Anthony :  Bayesian transfer learning between Gaussian process regression tasks , Proceedings of the IEEE International Symposium on Signal Processing and Information Technology 2019 (ISSPIT 2019), IEEE International Symposium on Signal Processing and Information Technology 2019 (ISSPIT 2019) /19./, (Ajman, AE, 20191209) [2019] Download DOI: 10.1109/ISSPIT47144.2019.9001885
  3. Papež Milan, Quinn Anthony :  Robust Bayesian transfer learning between Kalman filters , PROCEEDINGS OF MLSP 2019 : IEEE 29th International Workshop on Machine Learning for Signal Processing, 19 , IEEE 29th International Workshop on Machine Learning for Signal Processing, (Pittsburgh, US, 20191013) [2019] Download DOI: 10.1109/MLSP.2019.8918783
  4. Papež Milan :  Monte Carlo-Based Identification Strategies for State-Space Models, Vysoké učení technické v Brně, (Brno 2019) [2019] Download
  5. Papež Milan, Quinn Anthony :  Dynamic Bayesian knowledge transfer between a pair of Kalman filters , PROCEEDINGS OF MLSP 2018 : IEEE 28th International Workshop on Machine Learning for Signal Processing, 8517020 , International Workshop on Machine Learning for Signal Processing 2018 (MLSP 2018) /28./, (Aalborg, DK, 20180917) [2018] Download DOI: 10.1109/MLSP.2018.8517020
2019-01-07 08:39
Institute of Information Theory and Automation