Talks

Deep Learning and Reinforcement Learning Summer School 2018

2018- Deep Learning Summer School

Katherine A. Heller, Department of Statistical Science, Duke University
Title: Introduction to Machine Learning
Video

Hugo Larochelle, Google
Title: Neural Networks I
Video

David Duvenaud, Department of Computer Science, University of Toronto
Title: Autodiff
Video

Hugo Larochelle, Google
Title: Neural Networks II
Video

Jonathon Shlens, Google
Title: Introduction to Convolutional Neural Networks (CNNs)
Video

Sanja Fidler, Department of Computer Science, University of Toronto
Title: Advanced Deep Vision
Video

Balázs Kégl, Laboratoire de l Accélérateur Linéaire, University of Paris-Sud 11
Title: RAMP (Practical session)
Video

David Duvenaud, Department of Computer Science, University of Toronto
Title: Generative Models I
Video

Been Kim, Google
Title: Interpretability
Video

Sanjeev Arora, Department of Computer Science, Princeton University
Title: Theory
Video

Jimmy Ba, Department of Computer Science, University of Toronto
Title: Optimization I
Video

Jorge Nocedal, Robert R. McCormick School of Engineering and Applied Science, Northwestern University
Title: Optimization II
Video

Yoshua Bengio, Department of Computer Science and Operations Research, University of Montreal
Title: Recurrent Neural Networks (RNNs)
Video

Graham Neubig,  Language Technologies Institute, Carnegie Mellon University
Title: Language Understanding
Video

Jamie Kiros, Department of Computer Science, University of Toronto
Title: Multimodal Learning
Video

Blake Aaron Richards, Centre for the Neurobiology of Stress (CNS), University of Toronto Scarborough
Title: Computational Neuroscience
Video

Andrew Gordon Wilson, Department of Computer Science, Cornell University
Title: Bayesian Neural Nets
Video

Sageev Oore, Vector Institute
Title: Deep Learning and Music
Video

2018- Reinforcement Learning Summer School

Richard S. Sutton, Department of Computing Science, University of Alberta
Title: Introduction to RL and TD
Video

Sergey Levine, Department of Electrical Engineering and Computer Sciences, UC Berkeley
Title: Policy Search
Video

Amir-massoud Farahmand, Vector Institute
Title: Batch RL and ADP
Video

Martha White, Department of Computing Science, University of Alberta
Title: Off-Policy Learning
Video

Tor Lattimore, DeepMind Technologies Limited
Title: Bandits and Explore/Exploit in RL
Video

Doina Precup, School of Computer Science, McGill University
Title: Temporal Abstraction
Video

Emma Brunskill, Computer Science Department, Carnegie Mellon University
Title: Multi-task and Transfer in RL
Video

Marc G. Bellemare, Google
Title: Deep RL
Video

Hal Daumé III, Department of Computer Science, University of Maryland
Title: Imitation Learning
Video

Mohammad Ghavamzadeh, INRIA Lille – Nord Europe
Title: Safety in RL
Video

Michael Bowling, Department of Computing Science, University of Alberta
Title: Multi-agent RL
Video

VECTOR INSTITUTE MACHINE LEARNING ADVANCES AND APPLICATIONS SEMINAR

Presented at The Fields Institute

2017-18

Presented at Fields Institute

Barak Pearlmutter, Hamilton Institute, Maynooth
Near-Criticality and Pathology in the Central Nervous System
Abstract

Suchi Saria, Johns Hopkins University
Individualizing Healthcare with Machine Learning (Video)
Abstract

Peter Grünwald, Leiden University
Learning the learning rate: how to repair Bayes when the model is wrong (Video)
Abstract

Emma Brunskill, Stanford University
Reinforcement Learning When Experience is Expensive (Video)
Abstract

Josh Tenenbaum, Massachusetts Institute of Technology
Building machines that learn and think like humans (Video)
Abstract

Chris Maddison, University of Oxford
Relaxed Gradient Estimators (Video)
Abstract

Yair Weiss, Hebrew University
Learning the Statistics of Full Images (Video)
Abstract

Christopher Manning, Stanford University
Towards a better model for neural network reasoning (Video)
Abstract

Vlad Mnih, DeepMind
Efficient Multi-Task Deep Reinforcement Learning (Video)
Abstract

Stephen Friend, Sage Bionetworks
Exploring fundamental unknowns that prevent us from using our devices to navigate between disease and health (Video)
Abstract

Ilya Sutskever, OpenAI
Meta Learning and Self Play (Video)
Abstract

Yee Whye Teh, University of Oxford
DisTraL: Distill and Transfer for Deep Multitask Reinforcement Learning (Video)
Abstract

Guang Wei Yu (Layer 6), Mohammad Islam (Wattpad), Putra anggala (Shopify), and Javier Moreno (Rubikloud)
Recommendation Systems (Video)
Abstract

Jennifer Listgarten, Microsoft Research
From Genetics to CRISPR Gene Editing with Machine Learning (Video)
Abstract

Chris Williams, Univeristy of Edinburgh
Artificial Intelligence for Data Analytics (Video)
Abstract

Jon Shlens, Google Brain
Learning representations of the visual world
Abstract

Geoffrey Hinton, University of Toronto
What is wrong with convolutional neural nets? (Video)
Abstract

2016-2017

Presented at Fields Institute

David Sontag, Massachusetts Institute of Technology
How is Machine Learning Going to Change Health Care? (Video)
Abstract

Alex Graves, DeepMind
Frontiers in Recurrent Neural Network Research
Abstract

Max Welling, University of Amsterdam
Generalizing convolutions for Deep Learning (Video)
Abstract

Ernest Earon, Precision Hawk
Airborne Intelligence: Why birds are so good at what they do (Video)
Abstract

James Bergstra, Kindred
From Teleoperation to AGI (Video)
Abstract

Ryan Geriepy, ClearPath Robotics
3 Steps To Applying Machine Learning To Fleets Of Self-Driving Vehicles (Video)
Abstract

Shane Gu, Cambridge University
Sample-Efficient Deep Reinforcement Learning for Robotics (Video)
Abstract

David Blei, Columbia University
Probabilistic Topic Models and User Behavior (Video)
Abstract

Fernanda Viegas, Martin Wattenberg and Daniel Smilkov, Google
Visualization for machine learning–and human learning, too (Video)
Abstract

Roger Melko, University of Waterloo
Machine Learning Quantum Physics (Video)
Abstract

Pieter Abbeel, University of California, Berkeley
Deep Reinforcement Learning for Robotics (Video)
Abstract

Roger Grosse, University of Toronto
Optimizing neural networks using structured probabilistic models (Video)
Abstract

Graham Taylor, University of Guelph
Dataset Augmentation in Feature Space (Video)
Abstract

Rob Fergus, New York University / Facebook
Memory and Communication in Neural Networks (Video)
Abstract

Hugo Larochelle, Google Brain

Autoregressive Generative Models with Deep Learning (Video)

Abstract

Michael Schull, Institute for Clinical Evaluative Sciences
ICES: Linking data and discovery, and building a health data science agenda (Video)
Abstract

Alexandre Le Bouthillier, Imagia
Imagia: Artificial Intelligence for medical image analysis (Video)
Abstract

Brendan Frey, Deep Genomics
Deep Genomics: Changing the course of genomic medicine (Video)
Abstract

Joshua Landy, Figure 1
Figure 1: The computer will see you now (Video)
Abstract

Ofer Shai, Meta Inc.
Meta: Unlocking the world’s scientific and technical insights (Video)
Abstract

Roger Grosse, David Duvenaud and Sanja Fidler,, University of Toronto
Meet the New Faculty: Roger Grosse, David Duvenaud & Sanja Fidler (Video)
Abstract

Andrew McCallum, University of Massachusetts
Universal Schema for Representation and Reasoning from Natural Language (Video)
Abstract

Richard Sutton, University of Alberta
The Future of Artificial Intelligence Belongs to Search and Learning (Video)
Abstract

Geoffrey Hinton, University of Toronto
Using Fast Weights to Store Temporary Memories (Video)
Abstract

Amir Ban, Tel-Aviv University
When Should an Expert Make a Prediction? (Video)
Abstract

VECTOR FRIDAY ML SEMINAR

2019

Yaoliang Yu, University of Toronto
Deep Homogeneous Mixture Models: Representation, Separation and Approximation (Video)
Introduction
Vector Institute

Sheila McIlraith, University of Toronto
High-level Reward Function Specification in Reinforcement Learning (Video)
Introduction
Vector Institute

Babak Taati, University of Toronto
Introduction
Vector Institute

Yuri Boykov, University of Toronto
Image Segmentation without Full Supervision (Video)
Vector Institute

2018

Gillian Hadfield, University of Toronto
AI Alignment and Human Normativity (Video)
Introduction
Vector Institute

Scott Sanner, University of Toronto
Autoencoders for Collaborative Filtering (Video)
Introduction
Vector Institute

Peter Wittek, University of Toronto
Machine Learning on Near-Term Quantum Computers (Video)
Introduction
Vector Institute

Jesse Hoey, University of Waterloo
Affective Dynamics and Control in Group Processes (Video)
Introduction
Vector Institute

Andreas Moshovos, University of Toronto
Value-Based Deep Learning Hardware Acceleration (Video)
Introduction
Vector Institute

Micheal Brudno, University of Toronto
Improving Doctor-Patient Interaction with AI-Enabled Medical Note Taking (Video)
Introduction
Vector Institute

HEALTH AI ROUNDS

2018

Bartha Knoppers, McGill University
Data Sharing and the Human Right to Benefit From Science and its Applications (Video)
Vector Institute

Yin Aphinyanaphongs, NYU Langone Health
Clinical Predictive Analytics at NYU Langone Health (Video)
Introduction
Vector Institute

2019

Samantha Kleinberg, Stevens Institute of Technology
Large-scale causal inference in bio-medicine (Video)
Introduction
Vector Institute

ETHICS OF AI IN CONTEXT SERIES

2018

Presented at Centre of Ethics, University of Toronto

Richard Zemel, University of Toronto
Ensuring Fair and Responsible Automated Decisions (Video)
Centre of Ethics, University of Toronto

Frank Rudzicz, University of Toronto, University Health Network, Winterlight Labs
The Future of Automated Healthcare (Video)
Centre of Ethics, University of Toronto

Faculty

Faculty Affiliates

Yuhong Guo Suzanna Becker Neil Bruce Aleksandar Nikolov
Andreas Moshovos Blake Richards Gennady Pekhimenko Gillian Hadfield
Radford Neal Suzanne Stevenson Yang Xu Dana Kulic
Jimmy Lin Kate Larson Roger Melko Yaoliang Yu
Olga Veksler James Elder Jim Reilly John Connolly
Ranil Sonnadara Reza Samavi Thomas Doyle Konstantinos Derpanis
Alex Mihailidis Angela Schoellig Anne Martel Ashton Anderson
Babak Taati Benjamin Haibe-Kains Gerald Penn Graeme Hirst
Jason Anderson Kyros Kultulakos Michael Brudno Paul Boutros
Scott Sanner Sheila McIlrath Sven Dickinson Toniann Pitassi
Vaughn Betz Michael Hoffman Ali Ghodsi Jesse Hoey
Shai Ben-David Jody Culham Mark Daley Robert Mercer
Marcus Brubaker Yuri Boykov Ajay Agrawal Albert Yoon
Anthony Niblett Avi Goldfarb Benjamin Alarie Peter Wittek
Jonathan Kelly Maura Grossman Hui Jiang Hamid Reza Tizhoosh
Ruth Urner Tom Chau Laura Rosella

Postdocs

Mario Krenn Loic Roch Alina Selega Chendi Wang
Scott lowe Zacharie Naulet Faiza Khan Khattak Bo Zhao
Ethan Fetaya Marc Law Bradly Stadie Ali Ramezani-Kebrya
Joern Jacobson Shalmali Joshi Melissa McCradden Zamyla Chan
Linda Sunderman

Graduate Students and Student Interns

Chunhao Chang Mingjie Mai George Adam Ladislav Rampasek
Shems Saleh Sana Tonekaboni Daniel Hidru Lauren Erdman
Aziz Mezlini Angeline Yashodara Alexander Edmonds Ekansh Sharma
Christopher Srinivasa Haosui Duanmu Alex Gao Jeffrey Negrea
Jun Yang Yangbo Tang Jonathan Lorraine Geoffrey Roeder
Bowen Xu Tian Qi Chen Eric Langlois Chris Cremer
Will Grathwohl Guodong Zhang Jesse Bettencourt Matthew MacKay
Micha Livne Ali Punjani Fartash Faghri Farzaneh Mahdisoltani
Serena Jeblee Bai Li Mohamed Abdalla Akshay Budhkar
Demetres Kostas Daniyal Liaqat Fizza Ahmad Sheikh Stefania Raimondo
Arvid Fydenlund Ekaterina Kudashkina Thorsteinn Jonsson Colin Brennan
Vithursan Thangarasa Bradley Kennedy Alaaeldin Ali Shamak Dutta
Adam Balint Brendan Duke Angus Galloway Eu Wern Teh
Devinder Kumar Terrance Devries Michal Lisicki Boris Knyazev
Harris Chan Kaitlin Laverty Gurnit Atwal Kun Nie
Yulia Rubanova Alexander Sasse Nil Sahin Jeffrey Wintersinger
Simon Eng Amit Deshwar Kevin Ha Andrew Toulis
Ioan Andrei Barsan Chenxue Zhang Renjie Liao Eleni Triantafillou
Marc-Etienne Brunet David Madras Kamyar Seyed Ghasemipour Elliot Creager
Mengye Ren Jake Snell Kuan-Chieh Wang James Lucas
William Saunders Shengyang Sun Yuhuai  Wu Paul Adrian Vicol
Atef Chaudhury Amlan Kar Seung Wook Kim Jiaman  Li
Tingwu Wang Tingke Shen Wenzheng Chen Chaoqi  Wang
Hang Chu Kaustav Kundu Maria Shugrina Ricardo Salmon
Abdullah Rashwan Paulo Pachecho Priyank Jaini Joseph Scott
Jeffrey Rudd Guojun Zhang Ankit Vahdera Pan Pan Cheng
Kira Selby Rong Tian Tse Safwan Hossain John Chen
Haochen Zhang Soren Sabet Sarvestany Sheldon Huang Huan Ling
Gintare Karolina Dziugaite Rachid  Riad Kiarash Jamali Aidan Gomez
Sheng Jia Mufan Li YueLan Qin Ariel Herbert-Voss
Philippe Casgrain Nathan Killoran Oren Kraus Marissa Weis
Michael Leung Hannes Bretschneider Alice Gao
Romina Abachi Amir Hosein Khas Ahmadi Yuhao Zhou  

Postgraduate Affiliates – 2019-20 Cohort

Anastasia Razdaibiedina Anjali Silva Anna Golubeva Buser Say
Kyle Mills Lee Clement Lydia Y. Liu Lina Tran
Marie-Julie Favé Martin Magill Matthew Giamou Matthew J. S. Beach
Md Amirul Islam Michael Ridley Muhammad Raisul Alam Rafid Mahmood
Sayeh Sharifymoghaddam Xingyu Li Zhaleh Safikhani

Postgraduate Affiliates – 2018-19 Cohort

Tristan Aumentado-Armstrong Mahtab Ahmed Shazia Akbar Aryan Arbabi
Nabiha Asghar Ahmed Ashraf Seyed Ershad Banijamali Felix Berkenkamp
Rober Boshra Omar Boursalie Andrew Boutros Alberto  Camacho
Jaskiret    Dhindsa Elham Dolatabadi Mohamed Helwa Kathleen Houlahan
Ethan Jackson Mehran Karimzadeh Reghbati Shehroz Khan Jin Hee Kim
Dmitry Marin Sean Robertson Petr Smirnov Ian Smith
Laleh Soltan Ghoraie Robin Swanson Matthew Tesfaldet Rodrigo Andres  Toro Icarte
Stavros Tsogkas Ga Wu SiQi Zhou Mohammad Hassan Zokaei Ashtiani

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