Frequently Asked Questions

Mila is primarily a machine learning research center focused on deep learning and reinforcement learning. 

At Mila, we continually push the boundaries of cutting-edge research. Mila is best known for its scientific breakthroughs in deep learning, having contributed many of the first papers in the field, such as:

• introducing word embeddings in neural nets
• denoising autoencoders
• deep networks using ReLU instead of tanh or sigmoid functions self-attention and the consequential revolution in machine translation and natural language processing (NLP)
• generative adversarial networks (GANs)
• and more. 

Mila also published one of the most successful  textbooks on deep learning (MIT Press 2016) and co-founded the International Conference on Learning Representations (ICLR). 

Mila has been a hothouse for the development of deep reinforcement learning and the theoretical foundations of deep learning (mechanisms, optimization methods and analysis, generalization, in and out-of-distribution, causality, generative and probabilistic methods), building a critical mass of expertise at the intersection of theoretical neuroscience and deep learning (a.k.a neuro-AI), most recently by focusing on high-level conscious processing to help deep learning move from its current system 1 competence (intuitive knowledge) to a joint competence of system 1 and system 2 levels (verbalizable knowledge, reasoning, systematic generalization). 

Mila has also developed expertise in many application areas of machine learning (with a focus on AI for social good), from traditional areas such as computer vision, NLP and robotics to applications in healthcare (e.g., medical imaging, drug discovery), the environment (co-founding the Climate Change AI organization), AI4Science (to help modeling and discovery in physics, chemistry, biology, etc.) and social sciences (fighting sexual exploitation, contributing to the legal and philosophical aspects of Responsible AI, notably through the Montreal Declaration for the Responsible Development of AI).

Visit the Core Expertise page to learn more. 

Deep learning is a new and exciting field of research. A student with good mathematical skills can easily assimilate most of the central ideas of this field and quickly contribute to the research. Recently, deep learning has proven to be a resource-intensive field, with large neural networks powered by cutting-edge GPUs or distributed implementations making great leaps forward in object recognition and speech recognition. Deep learning research presents an unparalleled opportunity for students with strong mathematical backgrounds and programming skills to make a big impact.

Please visit the Supervision Requests page for more information about the supervision request process at Mila.

• A stimulating research environment: At Mila, we are passionate about the advancement of knowledge in the field of artificial intelligence. On any given day, you’ll find students discussing all kinds of ambitious research ideas. Our faculty is also very involved and engaged with the student community, which contributes to an interactive and open research climate.
• Work-life balance: At Mila, we produce quality research while maintaining a balance between work and personal life, a mindset deeply rooted in the Quebec culture. 
• Substantial computing resources: Mila students have access to several powerful computers equipped with GPUs. The institute’s resources are supplemented with access to shared computer clusters across Quebec and Canada.
• Opportunities to participate in conferences: Professors strongly encourage students to submit papers and  participate in conferences, viewing these events as an essential part of their training as researchers.
• Research funding: This type of funding is usually linked to industrial research projects that often lead to publications. Most students find this arrangement preferable to some of the arrangements at other universities where funded students must concede a significant portion of their work to non-research activities.
• Internships: Mila students regularly do internships at top industrial research groups around the world.

International students do need to pay additional fees, but Mila students supervised by a Mila affiliated member can usually have these costs covered by the research grants of their supervisor. They can also, when applicable, obtain a waiver for these fees.

Your supervisor will inform you of the financial assistance you will be granted. Your home university will also inform you ​​of your tuition waivers.