Program 2019

Lecture Slides

Afra Alishahi: Grounded Language Learning, from Sounds & Images to Meaning (and everything in between) (pdf)

Francis Bach: Large Scale Machine Learning Over Networks (pdf)

Alejandrina Cristià: Baby steps to language (pdf)

Alexei Efros: Self-Supervised Visual Learning and Synthesis (pdf)

Vipin Kumar: Big Data in Climate and Earth Sciences: Opportunities and Challenges in Machine Learning (pptx)

Jean-Paul Laumond: Mathematical foundations of robot motion (pptx)

Yann LeCun: Self-Supervised Learning (pdf)

Stéphane Mallat: Interpretable Deep Neural Networks (pdf)

Neils Peek: Predictive Analytics for Health and Care (pdf)

Patrick Pérez: Autonomous Driving and Sustainable Supervision (pdf)

Lenka Zdeborová: What has statistical physics to say about machine learning? (pdf)


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