Honestly this is one of the best introduction to the topic. A lot of the lectures directly dive / start with group theory and people without relevent background immediately loose interest seeing the mathematical concepts and axioms. This channel deserves more subs and views ❤❤
@sari547549 ай бұрын
You have a good ability to explain difficult subjects easily. There are tutorial videos for Geometric Deep Learning from Bronstein(who organized GDL tutorial school with Cohen, Burna etc) which includes this concept, but their tutorial needs more math background. Excellent.
@DeepFindr9 ай бұрын
Thank you!!
@jangradkowski2875 Жыл бұрын
I love your content, and often come back to recall important concepts. Thank you very much, and I hope that soon I will be able to afford to buy you a coffee.
@DeepFindr Жыл бұрын
Thank you, happy that it is useful :)
@Blueshockful Жыл бұрын
i've been looking at this topic these days, super helpful to wrap my head around better!
@DeepFindr Жыл бұрын
Awesome :)
@imolafodor4667 Жыл бұрын
hi, where the lower complexity of the network is stated as an advantage.. complex in what sense? my definition of complex network means there are more filters/neurons/weights to learn.. so how would equivariance reduce connections? those are fixed by our hand-crafted layer topology, no?
@spaceflame30 Жыл бұрын
Wonderful video, the examples are incredibly intuitive.
@Nocturnal813 Жыл бұрын
Awesome as always
@chinmay.prabhakar Жыл бұрын
Is it possible to share the slides as well?
@DeepFindr Жыл бұрын
Sure! Please send me a mail to deepfindr@gmail.com and I will attach them :)
@chinmay.prabhakar Жыл бұрын
@@DeepFindr Done. Hope to hear back from you soon :)
@user-wr4yl7tx3w Жыл бұрын
Really interesting content.
@gapsongg Жыл бұрын
Clean as fuck. Thank you very much. Nice visuals nice explanations. Easy to follow
@mathador4467 Жыл бұрын
Fantastic video, thx
@shaz-z506 Жыл бұрын
Nice video, could you please also create video of capsule networks, through caps-net you can also achieve equivariance in images.