default search action
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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:24 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: