Course Description

KeyNote and Courses

Keynotes

to be announced

Courses (to be completed)



  • Pierre Baldi
    (University of California, Irvine) [intermediate/advanced]
    Deep Learning: Theory, Algorithms, and Applications to the Natural Sciences


    Christopher Bishop
    (Microsoft Research Cambridge) [introductory]
    Introduction to the Key Concepts and Techniques of Machine Learning


    Aaron Courville
    (University of Montréal) [introductory/intermediate]
    Deep Generative Models


    Sergei V. Gleyzer
    (University of Florida) [introductory/intermediate]
    Feature Extraction, End-end Deep Learning and Applications to Very Large Scientific Data: Rare Signal Extraction, Uncertainty Estimation and Realtime Machine Learning Applications in Software and Hardware


    Tomas Mikolov
    (Facebook) [introductory]
    Using Neural Networks for Modeling and Representing Natural Languages (with Armand Joulin)


    Hermann Ney
    (RWTH Aachen University) [intermediate/advanced]
    Speech Recognition and Machine Translation: From Statistical Decision Theory to Machine Learning and Deep Neural Networks


    Navraj Pannu
    (GoDaddy) [introductory/intermediate]
    Deep Learning and Maximum Likelihood in Structural Biology