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720 Von Union

Thanks for sharing

Hi Jon, your talk about deep learning algorithms was interesting this is something I would like to learn more about. Did you apply your experimental models to the k space domain by regressing the images back into the data domain or were you able to use the raw data. I am concern with the pixelated under sampling (discussed at time point~5 min and 40s) is this is not something we could reproduce clinically. We can only fill k space linearly, concentrically or radially. The parallel undersampling is something we could mimic as we can opt to reduce k space filling in the phase encoding direction. I look forward to your response Kind regards Darren

Please can you send me the code for model . Thanks

❤

Inspiring talk, made me see things in a different way!

Nice topic, and very well presented, Tobias!

How does any of this stop the psychopaths taking over humanity from destroying it? Seems to be helping them IMO.

Thank you for the talk. It was super interesting. Cheers!

How to build this shape shifter concept using neural network ? ua-cam.com/video/ddFVypwsFSw/v-deo.html

Can you make a video about probabilistic functions and artificial neural networks? why to specifically take insipiration from neural network to solve probabilisting problrms ?

"PromoSM"

I find it difficult to understand the speaker's voice.

Great work!

@26:55 what is Y-hat????

I agree that this is a very good talk, and subtitles will help it to reach a wider audience...

really inspiring talk. hope the ppt could be uploaded as well. cheers!

I love this professor's presentation but it can sometimes be difficult to understand what he is saying. It would really help if there was a written transcript of the presentation.

Pᵣₒmₒˢᵐ

Look forward to more sessions about your current research, Dr. Yu. 🤩

Very interesting talk. Are there any easy to understand sources so I can learn more about the approaches Raul mentioned or about the field in general? So far I have always ignored noisiness of my data when training models.

Thanks for a very nice presentation on the topic!

slay kween

What sense does image segmentation make as a generative model problem? I imagine you could translate any problem into a generative model problem. E.g. instead of classification we can do generation of class conditioned on input image. Does formulating it in such a way makes more sense for image segmentation than for image classification or was that the point that any problem can be formulated this way?

🅿🆁🅾🅼🅾🆂🅼

This is what i need right now, thank you somuch

Thank you so much

Thanks for the nice talk!!

Merci

Am happy I finally got a permanent cure to my Herpes virus after taking the the medication I got from Dr oyakhire.