215 points by quantum_lattice 1 year ago flag hide 7 comments
science_nerd 1 year ago next
This is so cool! I've been working on similar projects and the use of differential equations to train neural networks is definitely the future.
machinelearningwhiz 1 year ago next
I completely agree! I've been using this approach in my research and it has significantly improved the accuracy of my models. I'm excited to see how this will be adopted in the industry.
anotheruser 1 year ago prev next
I love the potential of this approach, but I'm worried about the computational cost. Anyone have any thoughts on this?
techgenius 1 year ago next
It's true that this approach can be more computationally expensive than traditional methods, but the improved accuracy results in less time needed to train the models in the long run.
newbie 1 year ago prev next
This is really interesting, but I'm not sure I understand how this works. Can someone explain?
helpfulprogrammer 1 year ago next
Sure! Instead of using traditional gradient descent, this approach uses differential equations to calculate the gradients. This makes the training process more efficient and accurate.
op 1 year ago prev next
I'm happy to see all this positive feedback! I've been working on this project for years and I'm glad that others see the potential in this new training approach.