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Alejandro Molina 0001
Person information
- affiliation: TU Dortmund, Department of Computer Science, Germany
Other persons with the same name
- Alejandro Molina 0002 — Amazon, Seattle, WA, USA
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2020 – today
- 2024
- [c19]Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting:
Adaptive Rational Activations to Boost Deep Reinforcement Learning. ICLR 2024 - 2022
- [j5]Xiaoting Shao
, Alejandro Molina, Antonio Vergari
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140: 298-313 (2022) - [j4]Mikhail Fomichev
Next2You: Robust Copresence Detection Based on Channel State Information. ACM Trans. Internet Things 3(2): 11:1-11:31 (2022) - 2021
- [d15]Mikhail Fomichev
Index of Supplementary Files from "Next2You: Robust Copresence Detection Based on Channel State Information". Zenodo, 2021 - [d14]Mikhail Fomichev
Raw data from "Next2You: Robust Copresence Detection Based on Channel State Information". Zenodo, 2021 - [d13]Mikhail Fomichev
Evaluation results from "Next2You: Robust Copresence Detection Based on Channel State Information". Zenodo, 2021 - [i16]Quentin Delfosse, Patrick Schramowski, Alejandro Molina, Kristian Kersting:
Recurrent Rational Networks. CoRR abs/2102.09407 (2021) - [i15]Mikhail Fomichev, Luis F. Abanto-Leon, Max Stiegler, Alejandro Molina, Jakob Link, Matthias Hollick:
Next2You: Robust Copresence Detection Based on Channel State Information. CoRR abs/2111.05224 (2021) - 2020
- [j3]Benjamin Hilprecht, Andreas Schmidt
DeepDB: Learn from Data, not from Queries! Proc. VLDB Endow. 13(7): 992-1005 (2020) - [c18]Amos Treiber, Alejandro Molina, Christian Weinert
CryptoSPN: Expanding PPML beyond Neural Networks. PPMLP@CCS 2020: 9-14 - [c17]Amos Treiber, Alejandro Molina, Christian Weinert
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020: 1946-1953 - [c16]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 - [c15]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML 2020: 7563-7574 - [c14]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM 2020: 401-412 - [c13]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Residual Sum-Product Networks. PGM 2020: 545-556 - [i14]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-preserving Sum-Product Network Inference. CoRR abs/2002.00801 (2020) - [i13]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR abs/2004.06231 (2020)
2010 – 2019
- 2019
- [j2]Mikhail Fomichev, Max Maass
Perils of Zero-Interaction Security in the Internet of Things. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(1): 10:1-10:38 (2019) - [c12]Antonio Vergari, Alejandro Molina
Automatic Bayesian Density Analysis. AAAI 2019: 5207-5215 - [c11]Lukas Weber, Lukas Sommer
Resource-Efficient Logarithmic Number Scale Arithmetic for SPN Inference on FPGAs. FPT 2019: 251-254 - [c10]Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste:
Gaussian Lifted Marginal Filtering. KI 2019: 230-243 - [c9]Claas Völcker, Alejandro Molina, Johannes Neumann
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets. PKDD/ECML Workshops (1) 2019: 28-43 - [c8]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI 2019: 334-344 - [d12]Mikhail Fomichev
Results for scheme by Shrestha et al. from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d11]Mikhail Fomichev
Results for scheme by Truong et al. from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d10]Mikhail Fomichev
Results for scheme by Miettinen et al. from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d9]Mikhail Fomichev
Results for scheme by Schürmann and Sigg from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d8]Mikhail Fomichev
Results for scheme by Karapanos et al. from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d7]Mikhail Fomichev
Processed data from Mobile scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d6]Mikhail Fomichev
Processed data from Car scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d5]Mikhail Fomichev
Processed data from Office scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d4]Mikhail Fomichev
Raw data from Car scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d3]Mikhail Fomichev
Raw data from Office scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d2]Mikhail Fomichev
Raw data from Mobile scenario from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [d1]Mikhail Fomichev
Index of supplementary files from "Perils of Zero-Interaction Security in the Internet of Things". Zenodo, 2019 - [i12]Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting:
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR abs/1901.03704 (2019) - [i11]Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick:
Perils of Zero-Interaction Security in the Internet of Things. CoRR abs/1901.07255 (2019) - [i10]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR abs/1905.08550 (2019) - [i9]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. CoRR abs/1907.06732 (2019) - [i8]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Random Sum-Product Forests with Residual Links. CoRR abs/1908.03250 (2019) - [i7]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa
DeepDB: Learn from Data, not from Queries! CoRR abs/1909.00607 (2019) - 2018
- [c7]Alejandro Molina
Core Dependency Networks. AAAI 2018: 3820-3827 - [c6]Alejandro Molina
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI 2018: 3828-3835 - [c5]Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina
Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI 2018: 4163-4170 - [c4]Lukas Sommer, Julian Oppermann, Alejandro Molina
Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators. ICCD 2018: 350-357 - [c3]Stefan Lüdtke, Alejandro Molina
Gaussian Lifted Marginal Filtering. iWOAR 2018: 21:1-21:3 - [i6]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani:
Probabilistic Deep Learning using Random Sum-Product Networks. CoRR abs/1806.01910 (2018) - [i5]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. CoRR abs/1807.09306 (2018) - [i4]Moritz Kulessa
Model-based Approximate Query Processing. CoRR abs/1811.06224 (2018) - 2017
- [c2]Alejandro Molina
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. AAAI 2017: 2357-2363 - [i3]Alejandro Molina, Alexander Munteanu, Kristian Kersting:
Coresets for Dependency Networks. CoRR abs/1710.03285 (2017) - [i2]Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting:
Sum-Product Networks for Hybrid Domains. CoRR abs/1710.03297 (2017) - 2016
- [i1]Elena Erdmann, Karin Boczek
Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage. CoRR abs/1606.05110 (2016) - 2015
- [j1]Fabian Hadiji, Alejandro Molina
Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data. Mach. Learn. 100(2-3): 477-507 (2015) - [c1]Christoph Ide, Fabian Hadiji, Lars Habel, Alejandro Molina
LTE Connectivity and Vehicular Traffic Prediction Based on Machine Learning Approaches. VTC Fall 2015: 1-5
Coauthor Index
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