*DeepMind x UCL | Deep Learning Lectures | 11/12 | Modern Latent Variable Models* *My takeaways:* *1. Lecture outline **0:38* *2. Generative modeling **1:45* 2.1 Introduction of generative models 1:50 2.2 Progress in generative models 6:30 2.3 Types of generative models 8:00 *3. Latent variable models & inference **15:11* *4. Invertible models & exact inference **30:15* *5. Variational inference (VI) **41:47* *6. Gradient estimation in VI **1:10:25* *7. Variational autoencoders **1:22:15* *8. Conclusion **1:27:04*
@user-or7ji5hv8y4 жыл бұрын
best presentation on generative approach so far.
@SempoiGiler4 жыл бұрын
Thank you, really grateful for these kinds of educational videos, especially from a country where AI research can be considered non-existence. While I have a big desire to learn it. The knowledge shared is so precious to me. Thanks thanks thanks.
@bingeltube4 жыл бұрын
Unfortunately, Mnih provides very few references in video and slides
@colevfrank2 жыл бұрын
Superb lecture--very clear explanation of variational autoencoders and the associated tradeoffs between ease of inference and modeling flexibility/power
@freemind.d27144 жыл бұрын
The slides seem missing, please fix the link!
@youvenzful4 жыл бұрын
Big thanks for this incredible overview of latent variable models in a such short time presentation! Indeed, some additional material or literature recommendations on the subject could have been helpful.
@bryanbosire3 жыл бұрын
good work expounding on applications of statistical inference in generative models
@user-or7ji5hv8y4 жыл бұрын
thank you so much for posting these videos!
@user-or7ji5hv8y4 жыл бұрын
How about conjugate prior for tractability?
@learnml70344 жыл бұрын
Great presentation - very clear!
@user-or7ji5hv8y4 жыл бұрын
What is a factorial prior?
@lukn41003 жыл бұрын
Great lecture and big thanks to DeepMind for sharing this great content.
@patricknnamdi22034 жыл бұрын
This was great, thanks!
@tunestar4 жыл бұрын
Love the topic!! On to the lesson...
@tunestar4 жыл бұрын
Ok, it sucked! Why? Too much theory and math, very few practical examples.