Concept

Symbolic artificial intelligence

Publications associées (121)

Computational intelligence methods for the fatigue life modeling of composite materials

Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...

Elsevier2019

Exact Synthesis of LTL Properties from Traces

Heinz Riener

We present an exact approach to synthesize temporal-logic formulas in linear temporal logic (LTL) from a set of given positive and negative example traces. Our approach uses topology structures, in particular partial DAGs, to partition the search space int ...

IEEE2019

Logic Optimization of Majority-Inverter Graphs

Giovanni De Micheli, Mathias Soeken, Luca Gaetano Amarù, Eleonora Testa, Heinz Riener, Winston Jason Haaswijk

Majority-inverter graphs (MIGs) are a multi-level logic representation of Boolean functions with remarkable algebraic and Boolean properties that enable efficient logic optimizations beyond the capabilities of conventional logic representations. In this pa ...

VDE Verlag2019

Comment: Models Are Approximations!

Anthony Christopher Davison, Erwan Fabrice Koch, Jonathan Koh Boon Han

This discussion focuses on areas of disagreement with the papers, particularly the target of inference and the case for using the robust 'sandwich' variance estimator in the presence of moderate mis-specification. We also suggest that existing procedures m ...

INST MATHEMATICAL STATISTICS2019

A Domain-Adaptive Two-Stream U-Net for Electron Microscopy Image Segmentation

Pascal Fua, Mathieu Salzmann, Pablo Marquez Neila, Róger Bermúdez Chacón

Deep networks such as the U-Net are outstanding at segmenting biomedical images when enough training data is available, but only then. Here we introduce a Domain Adaptation approach that relies on two coupled U-Nets that either regularize or share correspo ...

2018

A Domain-Adaptive Two-Stream U-Net For Electron Microscopy Image Segmentation

Pascal Fua, Mathieu Salzmann, Pablo Marquez Neila

IEEE2018

Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance

Sylvain Calinon, Emmanuel Pignat

For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alterna ...

2018

Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance

Sylvain Calinon, Emmanuel Pignat

Idiap2018

Service-Oriented Business Design for IT students

Alain Wegmann, Blagovesta Hristova Kostova

In this Full Innovative Practice Paper, we present a teaching approach, based on service science, for integrating a business curriculum in the engineering educational program. Our approach is a composition of experiential learning, systems thinking, and se ...

IEEE2018

Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars

Davide Scaramuzza

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information. This paper presents a deep neural network approach that unlocks the potential of event cameras on a challenging motion-estima ...

2018

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