70 citations · 100 across the 6 of their papers we have counts for
11 papers
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs
Nimish Shah, Wannes Meert, Marian Verhelst
A growing number of applications like probabilistic machine learning, sparse linear algebra, robotic navigation, etc., exhibit irregular data flow computation that can be modeled w…
Acceleration of probabilistic reasoning through custom processor architecture
Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert +1
Probabilistic reasoning is an essential tool for robust decision-making systems because of its ability to explicitly handle real-world uncertainty, constraints and causal relations…
ProbLP: A framework for low-precision probabilistic inference
Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert +1
Bayesian reasoning is a powerful mechanism for probabilistic inference in smart edge-devices. During such inferences, a low-precision arithmetic representation can enable improved…
Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis
Machine learned models often must abide by certain requirements (e.g., fairness or legal). This has spurred interested in developing approaches that can provably verify whether a m…
A general anomaly detection framework for fleet-based condition monitoring of machines
Kilian Hendrickx, Wannes Meert, Yves Mollet +4
Machine failures decrease up-time and can lead to extra repair costs or even to human casualties and environmental pollution. Recent condition monitoring techniques use artificial…
An Automated Engineering Assistant: Learning Parsers for Technical Drawings
Dries Van Daele, Nicholas Decleyre, Herman Dubois +1
From a set of technical drawings and expert knowledge, we automatically learn a parser to interpret such a drawing. This enables automatic reasoning and learning on top of a large…