On Deep Learning and Multi-objective Shape Optimization

On Deep Learning and Multi-objective Shape Optimization

Optimization is a fundamental process in many scientific and engineering applications. Optimizing a function comprises searching its domain for an input that results in the minimum or maximum value of the given objective. In the case where we have access to an ...
10 SWISS ENGINEERING STARTUPS TO WATCH IN 2020

10 SWISS ENGINEERING STARTUPS TO WATCH IN 2020

We are happy to announce that we were selected by VentureLab as one of the 10 Swiss engineering start-ups to watch in 2020! You can see the whole article on https://www.venturelab.ch/10-Swiss-Engineering-Startups-to-Watch-in-2020
In-graph training loop

In-graph training loop

In a previous experiment, we have explored the behaviour and interaction between keras models, tf.functions, saved models and tf.dataset. A summary of this experiment is available here as a notebook. As a follow up to this previous test, we compared the performance of...
Deep Neural Network in simulations

Deep Neural Network in simulations

Deep learning and AI in general have taken the entire field of computer science by storm and has now become the dominant approach to solving a wide array of problems, ranging from winning board games to molecular discovery. However, Computer Assisted Design (CAD) and...
Artificial Intelligence meets Aerodynamics – the Ultimate Drone

Artificial Intelligence meets Aerodynamics – the Ultimate Drone

18 months ago, Neural Concept, EPFL (École polytechnique fédérale de Lausanne), senseFly and AirShaper teamed up for an academic research project to apply deep learning to aerodynamics. Neural Concept Shape was coupled with AirShaper to explore the space of designs,...
NeuralSampler: Euclidean Point Cloud Auto-Encoder and Sampler

NeuralSampler: Euclidean Point Cloud Auto-Encoder and Sampler

We propose an auto-encoder architecture that can both encode and decode clouds of arbitrary size and demonstrate its effectiveness at upsampling sparse point clouds. Interestingly, we can do so using less than half as many parameters as state-of-the-art architectures...

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