International Summer School on Deep Learning

Bilbao, Spain, July 17-21, 2017

DeepLearn 2017 Registration Form

(form version 1.11 courses)


  1. Either by bank transfer to:

    ActivoBank / Banco Sabadell
    Address: Príncipe de Vergara, 125, 28002 Madrid, Spain
    IBAN: ES96 0081 5965 3100 0238 5349
    account holder: C. Martin – GRLMC
    account holder’s address: Av. Catalunya 35, 43002 Tarragona, Spain

  2. Remarks: (1) Bank transfers should not involve any expense for the School. (2) Participants claiming early registration will be requested to prove that the bank transfer order was carried out by the deadline in case the fees arrive later.

  3. Or by PayPal.

  4. Remark: An extra fee of Euro 25 will be added automatically, to cover the transfer expenses PayPal will charge to the organizers.

General remarks concerning payment:
  • Mention DeepLearn 2017 and your name in the subject.
  • A receipt will be provided on site.
  • Participants registering on site must pay in cash. For the sake of local organization, however, it is much recommended to do it earlier.
  • Refunding of registration fees will not be possible unless the event is cancelled or a visa application gets rejected.

Registration deadlines and fees (all 23:59 CET)

Paid until Euro
January 27, 2017310 Euro
February 24, 2017340 Euro
March 24, 2017370 Euro
April 21, 2017400 Euro
May 19, 2017430 Euro
June 16, 2017460 Euro
Regular registration
July 14, 2017
490 Euro
On-site registration520 Euro

Fees comprise access to all courses and lunches.

Registration conditions

Please provide the following contact information: (bold fields are mandatory)!

1 The default values for City and Country fields are based on the client IP remote address. This information might be not very accurate (due to ISP policies, proxy connections, etc.), and we kindly ask you to provide the right values for the registration form.

First name and surname:

First name and surname in LaTeX:
(with accents, please)

(Prof., Dr., Mr., Mrs.)


(Professor, Researcher, PhD student, etc.)




Please provide the following academic background:

Degree (PhD, Masters, Bachelor, etc.):


Speciality (if any):

Registration Type:

490 Euro: Full

free: (only lecturers, organizers, and University of Deusto staff)

Please indicate maximum 8 courses you would tentatively like to attend.

Narendra Ahuja (University of Illinois, Urbana-Champaign), [introductory/intermediate] Basics of Deep Learning with Applications to Image Processing, Pattern Recognition and Computer Vision

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

Sven Behnke (University of Bonn), [intermediate] Visual Perception using Deep Convolutional Neural Networks

Mohammed Bennamoun (University of Western Australia), [introductory/intermediate] Deep Learning for Computer Vision

Hervé Bourlard (Idiap Research Institute), [intermediate/advanced] Deep Sequence Modeling: Historical Perspective and Current Trends

Thomas Breuel (NVIDIA Corporation),[intermediate] Segmentation, Processing, and Tracking, with Applications to Video, Gaming, VR, and Self-driving Cars

George Cybenko (Dartmouth College), [intermediate] Deep Learning of Behaviors

Rina Dechter (University of California, Irvine), [introductory] Algorithms for Reasoning with Probabilistic Graphical Models

Li Deng (Citadel), [introductory/advanced] An Overview of Deep Learning for Speech, Image, Text, and Multi-modal Processing

Jianfeng Gao (Microsoft Research), [introductory/intermediate] An Introduction to Deep Learning for Natural Language Processing

Michael Gschwind (IBM T.J. Watson Research Center), [introductory/intermediate] Deploying Deep Learning Applications at the Enterprise Scale

Yufei Huang (University of Texas, San Antonio), [intermediate/advanced] Deep Learning for Precision Medicine and Biomedical informatics

Soo-Young Lee (Korea Advanced Institute of Science and Technology), [intermediate/advanced] Multi-modal Deep Learning for the Recognition of Human Emotions in the Wild

Li Erran Li (Columbia University), [intermediate/advanced] Deep Reinforcement Learning: Recent Advances and Frontiers

Michael C. Mozer (University of Colorado, Boulder), [introductory/intermediate] Incorporating Domain Bias into Neural Networks

Roderick Murray-Smith (University of Glasgow), [intermediate] Applications of Deep Learning Models in Human-Computer Interaction Research

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

Jose C. Principe (University of Florida), [intermediate/advanced] Cognitive Architectures for Object Recognition in Video

Marc'Aurelio Ranzato (Facebook AI Research), [introductory/intermediate] Learning Representations for Vision, Speech and Text Processing Applications

Maximilian Riesenhuber (Georgetown University), [introductory/intermediate] Deep Learning in the Brain

Ruslan Salakhutdinov (Carnegie Mellon University), [intermediate/advanced] Foundations of Deep Learning and its Recent Advances

Alessandro Sperduti (University of Padua), [intermediate/advanced] Deep Learning for Sequences

Jimeng Sun (Georgia Institute of Technology), [introductory] Interpretable Deep Learning Models for Healthcare Applications

Julian Togelius (New York University), [intermediate] (Deep) Learning for (Video) Games

Joos Vandewalle (KU Leuven), [introductory/intermediate] Data Processing Methods, and Applications of Least Squares Support Vector Machines

Ying Nian Wu (University of California, Los Angeles), [introductory/intermediate] Deep Generative Models and Unsupervised Learning

Eric P. Xing (Carnegie Mellon University), [intermediate/advanced] Statistical Machine Learning Perspectives of Extending Deep Neural Networks: Kernels, Logics, Regularizers, Priors, and Distributed Algorithms

Georgios N. Yannakakis (University of Malta), [introductory/intermediate] Deep Learning for Games - But not for Playing them

Scott Wen-tau Yih (Microsoft Research), [introductory/intermediate] Continuous Representations for Natural Language Understanding

Richard Zemel (University of Toronto), [introductory/intermediate] Learning to Understand Images and Text

Supplementary information:

Arriving Date:

Departure Date:

Notes for organizers:

Acknowledgement and Copyright Notice

To get City and Country information we use the GeoLite City databases, and the free server library provided by MaxMind (Copyright (c) 2008 MaxMind, Inc.) for which there is an OPEN DATA LICENSE.

This product includes GeoLite data created by MaxMind, available from