Valais/Wallis AI Workshop 5th edition


May 3rd 2019

@ Idiap Research Institute, Room 106

Valais/Wallis AI Workshop 5th edition

Interpreting Machine Learning

Machine learning has become an integral part of many fields of research and has achieved considerable success. Despite continued advancements made, it is not always explainable: (a) what information is the machine learning from the data? and (b) how is the machine making the decisions? The 5th edition of Valais/Wallis AI workshop focuses on these questions by engaging researchers from various fields through presentations and discussions.


Find hereafter the talk of the Keynote speaker Prof. Pena Carlos Andrés from HEIG-VD.

To watch all the workshop's talks, please click on the links below.

Keynote speech: Prof. Pena Carlos Andrés, HEIG-VD Methods for Rule and Knowledge Extraction from Deep Neural Networks - Q&A

Hannah Muckenhirn, Idiap Research Institute Visualizing and understanding raw speech modeling with convolutional neural networks - Q&A

Mara Graziani, HES-SO Valais-Wallis Concept Measures to Explain Deep Learning Predictions in Medical Imaging

Suraj Srinivas, Idiap Research Institute What do neural network saliency maps encode?

Dr Vincent Andrearczyk, HES-SO Valais-Wallis Transparency of rotation-equivariant CNNs via local geometric priors - Q&A

Dr Sylvain Calinon, Idiap Research Institute Interpretable models of robot motion learned from few demonstrations - Q&A

Xavier Ouvrard, University of Geneva / CERN The HyperBagGraph DataEdron: An Enriched Browsing Experience of Scientific Publication Databa

Seyed Moosavi from Signal Processing Laboratory 4 (LTS4), EPFL Improving robustness to build more interpretable classifiers - Q&A

Sooho Kim from UniGe Interpretation of End-to-end one Dimension Convolutional Neural Network for Fault Diagnosis on a Planetary Gearbox

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