68 citations · 117 across the 5 of their papers we have counts for
5 papers
VEDLIoT -- Next generation accelerated AIoT systems and applications
Kevin Mika, René Griessl, Nils Kucza +29
The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propo…
VEDLIoT: Very Efficient Deep Learning in IoT
Martin Kaiser, Rene Griessl, Nils Kucza +33
The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also deali…
LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
B. Salami, K. Parasyris, A. Cristal +42
The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engi…
Bayesian optimization in ab initio nuclear physics
A. Ekström, C. Forssén, C. Dimitrakakis +5
Theoretical models of the strong nuclear interaction contain unknown coupling constants (parameters) that must be determined using a pool of calibration data. In cases where the mo…
Word Sense Disambiguation using a Bidirectional LSTM
Mikael Kågebäck, Hans Salomonsson
In this paper we present a clean, yet effective, model for word sense disambiguation. Our approach leverage a bidirectional long short-term memory network which is shared between a…