Portrait of Chris Pal

Chris Pal

Core Academic Member
christopher.pal@mila.quebec
Canada CIFAR AI Chair
Full Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering
Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research
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Biography

Christopher Pal is a Canada CIFAR AI Chair, full professor at Polytechnique Montréal and adjunct professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. He is also a Distinguished Scientist at ServiceNow Research.

Pal has been involved in AI and machine learning research for over twenty-five years and has published extensively on large-scale language modelling methods and generative modelling techniques. He has a PhD in computer science from the University of Waterloo.

Current Students

Shubham Agarwal
Postdoctorate - HEC Montréal
Principal supervisor :
Laurent Charlin
shubham.agarwal@mila.quebec
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Paul Barde
PhD - McGill University
Principal supervisor :
Derek Nowrouzezahrai
bardepau@mila.quebec
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Chris Beckham
PhD - Polytechnique Montréal
christopher.beckham@mila.quebec
Georges Belanger Albarran
Master's Research - Université de Montréal
georges.belangeralbarran@mila.quebec
Simon Chamorro
Master's Research - Polytechnique Montréal
chamorrs@mila.quebec
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Can (Sam) Chen
PhD - McGill University
Principal supervisor :
Xue (Steve) Liu
can.chen@mila.quebec
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Amine El-hattami
PhD - Polytechnique Montréal
elhattaa@mila.quebec
Chris Emezue
Master's Research - Université de Montréal
Co-supervisor :
Derek Nowrouzezahrai
chris.emezue@mila.quebec
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Matthew Fortier
Master's Research - Polytechnique Montréal
matthew.fortier@mila.quebec
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Roger Girgis
PhD - Polytechnique Montréal
girgisro@mila.quebec
Anthony Gosselin
Master's Research - Polytechnique Montréal
anthony.gosselin@mila.quebec
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Simon Guiroy
PhD - Université de Montréal
Co-supervisor :
Sarath Chandar Anbil Parthipan
guiroys@mila.quebec
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Abhinav Gupta
PhD - Université de Montréal
guptaabh@mila.quebec
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Baudchon Hugo Baudchon
Collaborating researcher - Université de Montréal
Principal supervisor :
Étienne Laliberté
hugo.baudchon@mila.quebec
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Jae Hyun Lim
PhD - Université de Montréal
limjaehy@mila.quebec
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Michelle Lin
Collaborating researcher
michelle.lin@mila.quebec
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Ge Ya (olga Luo) Luo
PhD - Université de Montréal
xugeya@mila.quebec
Z Luo
PhD - Polytechnique Montréal
luozhiha@mila.quebec
Abdou Mousas
PhD - Université de Montréal
mousasab@mila.quebec
Alexandre Piché
PhD - Université de Montréal
picheale@mila.quebec
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Jonathan Pilault
PhD - Polytechnique Montréal
pilaultj@mila.quebec
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Mats Leon Richter
Postdoctorate - Université de Montréal
mats-leon.richter@mila.quebec
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Juan Rodriguez
PhD - École de technologie suprérieure
juan.rodriguez@mila.quebec
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Luke Rowe
PhD - Université de Montréal
Principal supervisor :
Liam Paull
luke.rowe@mila.quebec
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Julien Roy
PhD - Polytechnique Montréal
Co-supervisor :
Pierre-Luc Bacon
royjulie@mila.quebec
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Aditya Sharma
PhD
Principal supervisor :
Amal Zouaq
aditya.sharma@mila.quebec
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Mattie Tesfaldet
PhD - McGill University
Principal supervisor :
Derek Nowrouzezahrai
mattie.tesfaldet@mila.quebec
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Vikram Voleti
PhD - Université de Montréal
voletivi@mila.quebec
Martin Weiss
PhD - Polytechnique Montréal
weissmar@mila.quebec
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Publications

Theano: A Python framework for fast computation of mathematical expressions
Rami Al-rfou'
Guillaume Alain
Amjad Almahairi
Christof Angermüller
Dzmitry Bahdanau
Nicolas Ballas
Frédéric Bastien
Justin S. Bayer
A. Belikov
A. Belopolsky
Yoshua Bengio
Arnaud Bergeron
James Bergstra
Valentin Bisson
Josh Bleecher Snyder
Nicolas Bouchard
Nicolas Boulanger-Lewandowski
Xavier Bouthillier
Alexandre De Brébisson
Olivier Breuleux … (see 92 more)
pierre luc carrier
Kyunghyun Cho
Jan Chorowski
Paul F. Christiano
Tim Cooijmans
Marc-Alexandre Côté
Myriam Côté
Aaron Courville
Yann Dauphin
Olivier Delalleau
Julien Demouth
Guillaume Desjardins
Sander Dieleman
Laurent Dinh
M'elanie Ducoffe
Vincent Dumoulin
Samira Ebrahimi Kahou
Dumitru Erhan
Ziye Fan
Orhan Firat
Mathieu Germain
Xavier Glorot
Ian G Goodfellow
Matthew Graham
Caglar Gulcehre
Philippe Hamel
Iban Harlouchet
Jean-philippe Heng
Balázs Hidasi
Sina Honari
Arjun Jain
Sébastien Jean
Kai Jia
Mikhail V. Korobov
Vivek Kulkarni
Alex Lamb
Pascal Lamblin
Eric Larsen
César Laurent
S. Lee
Simon-mark Lefrancois
Simon Lemieux
Nicholas Léonard
Zhouhan Lin
J. Livezey
Cory R. Lorenz
Jeremiah L. Lowin
Qianli M. Ma
Pierre-Antoine Manzagol
Olivier Mastropietro
R. McGibbon
Roland Memisevic
Bart van Merriënboer
Vincent Michalski
Mehdi Mirza
Alberto Orlandi
Chris Pal
Razvan Pascanu
Mohammad Pezeshki
Colin Raffel
Daniel Renshaw
Matthew David Rocklin
Adriana Romero Soriano
Markus Dr. Roth
Peter Sadowski
John Salvatier
Francois Savard
Jan Schlüter
John D. Schulman
Gabriel Schwartz
Iulian V. Serban
Dmitriy Serdyuk
Samira Shabanian
Etienne Simon
Sigurd Spieckermann
S. Subramanyam
Jakub Sygnowski
Jérémie Tanguay
Gijs van Tulder
Joseph Turian
Sebastian Urban
Pascal Vincent
Francesco Visin
Harm de Vries
David Warde-Farley
Dustin J. Webb
M. Willson
Kelvin Xu
Lijun Xue
Li Yao
Saizheng Zhang
Ying Zhang
Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficie… (see more)ntly. Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements. Theano is being actively and continuously developed since 2008, multiple frameworks have been built on top of it and it has been used to produce many state-of-the-art machine learning models. The present article is structured as follows. Section I provides an overview of the Theano software and its community. Section II presents the principal features of Theano and how to use them, and compares them with other similar projects. Section III focuses on recently-introduced functionalities and improvements. Section IV compares the performance of Theano against Torch7 and TensorFlow on several machine learning models. Section V discusses current limitations of Theano and potential ways of improving it.
2016-05-09
ArXiv (preprint)
arxiv.org
arxiv.org