The 2020 Deep Learning Reinforcement Learning Summer School is going virtual

August 3rd – August 7, 2020

The 2020 Deep Learning Reinforcement Learning Summer School is going virtual! The DLRL will take place August 3rd – August 7, 2020.

The week-long Summer School offers exciting topics with world-renowned speakers, daily breakout sessions, and 1:1’s with speakers. A typical day will run from 10:30am to 4pm (Eastern Time), followed by breakouts and socials. 

Applications are closed. All 2020 applicants will automatically be transferred to the 2021 edition hosted in Montréal by Mila & CIFAR.

Accepted applicants for the virtual Summer School will be contacted in the coming weeks.

About the CIFAR Deep Learning and Reinforcement Learning School 

In 2005, CIFAR’s Learning in Machines & Brains program hosted its first Deep Learning and Reinforcement Learning Summer School in Toronto with the goal of fostering the next generation of AI researchers. Many of the former students are now leaders at some of the top tech firms and university labs.

Today, the DLRL Summer School is a part of both the CIFAR Learning in Machines & Brains program and CIFAR Pan-Canadian AI Strategy’s National Program of Activities, and is delivered in partnership with Canada’s three national AI Institutes, Mila, Amii and the Vector Institute.

2019 CIFAR Deep Learning & Reinforcement Learning Summer School Highlights

Deep Learning Summer School (DLSS)

Deep neural networks are a powerful method for automatically learning distributed representations at multiple levels of abstraction. Over the past decade, they have dramatically pushed forward the state-of-the-art in domains as diverse as vision, language understanding, robotics, game playing, graphics, health care, and genomics. The DLSS will cover both the foundations and applications of deep neural networks, from fundamental concepts to leading-edge research results.

Reinforcement Learning Summer School (RLSS)

Reinforcement Learning is a family of approaches for developing systems that learn optimal behaviour through interaction with an environment. In recent years, reinforcement learning has seen success as an essential component of Deep Reinforcement Learning, which has helped AI researchers achieve previously unheard of results in games like Go and in the development of autonomous vehicles. The RLSS will cover the basics of reinforcement learning and show its most recent research trends and discoveries, as well as present an opportunity to interact with graduate students and senior researchers in the field.

About the 2020 CIFAR DLRL Summer School Edition

This year’s DLRL Summer School happens August 3 – 7, 2020 at Mila, the Quebec Artificial Intelligence Institute in Montreal, Quebec, Canada.

The event brings together graduate students, post-docs and professionals to cover the foundational research, new developments, and real-world applications of deep learning and reinforcement learning. 

In numbers


The CIFAR DLRLSS hosts 250 attendees.


Over 20 countries are represented yearly at the CIFAR DLRLSS event.


The 2020 DLRLSS edition is hosted in collaboration with over 20 of the most prominent leaders in the fields of deep learning and reinforcement learning.

Our Speakers

The CIFAR DLRL Summer School is a unique occasion for participants to connect with and learn directly from some of the world’s most renowned researchers and lecturers.


“We are very excited to welcome the next generation of AI experts from around the world to Montreal. The Summer School is a privileged opportunity to provide training, but also to engage in discussions and create meaningful opportunities for collaboration among researchers. ”


– Yoshua Bengio, Scientific Director at Mila

The 2020 DLRLSS is hosted by CIFAR and Mila, with participation and support from the Alberta Machine Intelligence Institute (Amii) and the Vector Institute.

Crédit photo: Maryse Boyce

About Mila

Located in the heart of Quebec’s Artificial Intelligence ecosystem, Mila is a community of 450 researchers specializing in machine learning and dedicated to scientific excellence and innovation. Our mission is to be a global pole for scientific advances that inspires innovation and the development of AI for the benefit of all.

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