32 citations · 194 across the 16 of their papers we have counts for
17 papers
Donor-acceptor discrete optical emission in 2D perovskites
Setatira Gorji, Marie Krecmarova, Alejandro Molina +12
Two-dimensional (2D) van der Waals nanomaterials have attracted considerable attention for potential use in photonic and optoelectronic applications in the nanoscale, due to their…
Next2You: Robust Copresence Detection Based on Channel State Information
Mikhail Fomichev, Luis F. Abanto-Leon, Max Stiegler +3
Context-based copresence detection schemes are a necessary prerequisite to building secure and usable authentication systems in the Internet of Things (IoT). Such schemes allow one…
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Quentin Delfosse, Patrick Schramowski, Martin Mundt +2
Latest insights from biology show that intelligence not only emerges from the connections between neurons but that individual neurons shoulder more computational responsibility tha…
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
Robert Peharz, Steven Lang, Antonio Vergari +6
Probabilistic circuits (PCs) are a promising avenue for probabilistic modeling, as they permit a wide range of exact and efficient inference routines. Recent ``deep-learning-style'…
CryptoSPN: Privacy-preserving Sum-Product Network Inference
Amos Treiber, Alejandro Molina, Christian Weinert +2
AI algorithms, and machine learning (ML) techniques in particular, are increasingly important to individuals' lives, but have caused a range of privacy concerns addressed by, e.g.,…
DeepDB: Learn from Data, not from Queries!
Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa +3
The typical approach for learned DBMS components is to capture the behavior by running a representative set of queries and use the observations to train a machine learning model. T…