Követés
Alejandro Molina
Alejandro Molina
Amazon
E-mail megerősítve itt: amazon.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Deepdb: Learn from data, not from queries!
B Hilprecht, A Schmidt, M Kulessa, A Molina, K Kersting, C Binnig
arXiv preprint arXiv:1909.00607, 2019
3112019
Mixed sum-product networks: A deep architecture for hybrid domains
A Molina, A Vergari, N Di Mauro, S Natarajan, F Esposito, K Kersting
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
1382018
Einsum networks: Fast and scalable learning of tractable probabilistic circuits
R Peharz, S Lang, A Vergari, K Stelzner, A Molina, M Trapp, ...
International Conference on Machine Learning, 7563-7574, 2020
1372020
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ...
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
1372019
Pad\'e Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
A Molina, P Schramowski, K Kersting
International Conference on Learning Representations, 2020
952020
Spflow: An easy and extensible library for deep probabilistic learning using sum-product networks
A Molina, A Vergari, K Stelzner, R Peharz, P Subramani, N Di Mauro, ...
arXiv preprint arXiv:1901.03704, 2019
682019
Conditional sum-product networks: Imposing structure on deep probabilistic architectures
X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting
International Conference on Probabilistic Graphical Models, 401-412, 2020
502020
LTE connectivity and vehicular traffic prediction based on machine learning approaches
C Ide, F Hadiji, L Habel, A Molina, T Zaksek, M Schreckenberg, K Kersting, ...
2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), 1-5, 2015
502015
Poisson sum-product networks: A deep architecture for tractable multivariate poisson distributions
A Molina, S Natarajan, K Kersting
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
492017
Automatic Bayesian density analysis
A Vergari, A Molina, R Peharz, Z Ghahramani, K Kersting, I Valera
Proceedings of the AAAI Conference on Artificial Intelligence 33, 5207-5215, 2019
432019
Poisson dependency networks: Gradient boosted models for multivariate count data
F Hadiji, A Molina, S Natarajan, K Kersting
Machine Learning 100, 477-507, 2015
422015
Automatic mapping of the sum-product network inference problem to fpga-based accelerators
L Sommer, J Oppermann, A Molina, C Binnig, K Kersting, A Koch
2018 IEEE 36th International Conference on Computer Design (ICCD), 350-357, 2018
382018
Probabilistic deep learning using random sum-product networks
R Peharz, A Vergari, K Stelzner, A Molina, M Trapp, K Kersting, ...
arXiv preprint arXiv:1806.01910, 2018
372018
Perils of zero-interaction security in the internet of things
M Fomichev, M Maass, L Almon, A Molina, M Hollick
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019
342019
Core dependency networks
A Molina, A Munteanu, K Kersting
Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI …, 2018
332018
Sum-product autoencoding: Encoding and decoding representations using sum-product networks
A Vergari, R Peharz, N Di Mauro, A Molina, K Kersting, F Esposito
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
282018
Öffentlichkeitsorientierung von Wissenschaftsinstitutionen und Wissenschaftsdisziplinen
J Serong, L Koppers, E Luschmann, A Molina Ramirez, K Kersting, ...
Publizistik 62 (2), 153-178, 2017
282017
Conditional sum-product networks: Modular probabilistic circuits via gate functions
X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting
International Journal of Approximate Reasoning 140, 298-313, 2022
202022
Adaptive rational activations to boost deep reinforcement learning
Q Delfosse, P Schramowski, M Mundt, A Molina, K Kersting
arXiv preprint arXiv:2102.09407, 2021
19*2021
Model-based approximate query processing
M Kulessa, A Molina, C Binnig, B Hilprecht, K Kersting
arXiv preprint arXiv:1811.06224, 2018
192018
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