Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Self-Supervised Learning and Variational Inference

Alfredo Canziani via YouTube

Overview

Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
This lecture examines self-supervised learning through sparse modeling, amortized inference, group sparsity, recurrent sparse autoencoders, and temporal consistency. It concludes with intuitive and probabilistic interpretations of variational autoencoders.

Syllabus

– Welcome to class
– GANs revisited
– Self-supervised learning: a broader purpose
– Sparse modeling
– Amortized inference
– Convolutional sparse modeling with group sparsity
– Discriminant recurrent sparse AE
– Other self-supervised learning techniques
– Group sparsity
– Regularization through temporal consistency
– VAE: intuitive interpretation
– VAE: probabilistic variational approximation-based interpretation

Taught by

Alfredo Canziani

Reviews

Start your review of Self-Supervised Learning and Variational Inference

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.