Hierarchical Decompositional Mixtures of Variational Autoencoders
Autorzy:
Ping Liang Tan and Robert Peharz
Opublikowane w:
Proceedings of the 36th International Conference on Machine Learning (ICML), Numer 36, 2019, Strona(/y) 6115--6124
Wydawca:
Proceedings of Machine Learning Research
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Autorzy:
Havasi, Marton; Peharz, Robert; Hernández-Lobato, José Miguel
Opublikowane w:
International Conference on Learning Representations, ICLR 2019, Numer 7, 2019, Strona(/y) --
Wydawca:
OpenReview.net
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
Autorzy:
Karl Stelzner, Robert Peharz and Kristian Kersting
Opublikowane w:
Proceedings of the 36th International Conference on Machine Learning (ICML), Numer 36, 2019, Strona(/y) 5966--5975
Wydawca:
Proceedings of Machine Learning Research (PMLR)
Automatic Bayesian Density Analysis
(odnośnik otworzy się w nowym oknie)
Autorzy:
Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
Opublikowane w:
Proceedings of the AAAI Conference on Artificial Intelligence, Numer 33, 2019, Strona(/y) 5207-5215, ISSN 2374-3468
Wydawca:
AAAI Press
DOI:
10.1609/aaai.v33i01.33015207
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
Autorzy:
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting and Zoubin Ghahramani
Opublikowane w:
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, (UAI), Numer 35, 2019, Strona(/y) --
Wydawca:
AUAI Press
Bayesian Learning of Sum-Product Networks
Autorzy:
Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
Opublikowane w:
Advances in Neural Information Processing Systems, Numer 32, 2019, Strona(/y) 6344--6355
Wydawca:
Curran Associates, Inc.
Deep Structured Mixtures of Gaussian Processes
Autorzy:
Martin Trapp, Robert Peharz, Franz Pernkopf, Carl E. Rasmussen
Opublikowane w:
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), Numer 1, 2020, Strona(/y) accepted, in print
Wydawca:
Proceedings of Machine Learning Research
