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Alireza Makhzani

Appointment

Canada CIFAR AI Chair

Pan-Canadian AI Strategy

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About

Alireza Makhzani is a Canada CIFAR AI Chair at the Vector Institute and an adjunct professor at the Department of Electrical and Computer Engineering at the University of Toronto.

Makhzani’s research interests intersect with unsupervised learning and generative models. He has previously developed adversarial inference methods for learning generative models.

Relevant Publications

  • Severo, D., Townsend, J., Khisti, A., Makhzani, A., & Ullrich, K. (2021). Compressing Multisets with Large Alphabets.

  • Brekelmans, R., Nielsen, F., Makhzani, A., Galstyan, A., & Steeg, G. V. (2020). Likelihood ratio exponential families.

  • Huang, S., Makhzani, A., Cao, Y., & Grosse, R. (2020). Evaluating lossy compression rates of deep generative models. In International Conference on Machine Learning (pp. 4444-4454). PMLR.

  • Makhzani, A., & Frey, B. (2017). Pixelgan autoencoders.

  • Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., & Frey, B. (2015). Adversarial autoencoders.

Institution

University of Toronto

Vector Institute

Department

Electrical and Computer Engineering

Education

  • PhD (Electrical and Computer Engineering), University of Toronto

Country

Canada

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