I wonder how lucky are we. Viewing world class lectures from Indian village. That too without any cost. Thank you

Thanks for the video. The concept introduced in 2016 is like using dictionaries for dynamical systems and the follow up papers extends this work. Great work.

Wow, this is such a great lecture. Thank you. I came for RL but I am staying for interpretable and generalizable models.

One of the best videos I've seen! It's amazing!

Spectacular work, thank you for sharing.

Great Lecture sir, eagerly Waiting for Lagrangian coherent structure series

Very nice lecture

Thank you for your teaching, really good education for parametric architect, engineer like me, I really the chaos theory, Lorentz attractor & aerodynamics 👍👍👍🥂🦋✨

Oh god I absolute loved this!

Brilliant as always

Wow, I’ve done similar model fitting. Stepwise fitting does well to form a sparse model excluding parameters which are not physically involved. The challenge is identify the cutoff point where more parameters are not added.

Although randomness had often been viewed as an obstacle and a nuisance for many centuries, in the 20th century computer scientists began to realize that the deliberate introduction of randomness into computations can be an effective tool for designing better algorithms. In some cases, such randomized algorithms even outperform the best deterministic methods.

gotta be honest steve. I'm disappointed that you didn't start with "welcome back" that's half of the reason I watch your videos

Great video! I was waiting for it. But my major doubt with syndy is finding the right base. In the future, you could make a lecture focus in ways to find the bases because this look like the greatest challenge.

Really impressive and inspiring stuff! Thanks for sharing…it definitely stimulates ideas

Very interesting novel application! Expect some more app for the coupled with PB ..... in future:)

Especially curious about the neuroscience applications. Maybe think also of other biological systems: immune system, virus evolution, ...

Thank you for this very interesting lecture ! I should be starting a PhD in Applied Maths for Hydrology in the next few months and I would really like to apply POD+constrained SINDy methods for solving inverse problems on St-Venant equations. Do you think the PySindy library can be used to build easy-to-invert models for data assimilation ? Thank you again for what you are doing, I’m a huge fan of your work ! Have a nice day.

How does sindy compare with genetic programming for system identification?

Can these techniques be used for things like weather or climate simulations? Or are those too "chaotic" for sparse models to work?

Please come speak at my school Rochester Institute of Technology. I am part of the Ph.D. program for Mathematical Modeling and it would be sick!

Hey Steve, is this just a shorter version of the talk you did for 'critical transitions with complex systems'?

Really interesting... do you have plans to apply sindy to telecom network traffic analytics?

Where is the link for the video on sindy + autoencoders

First of all, thank you very much for sharing your knowledge and your great presentations. I am interested in the problem of three cylinders (min 20) I could not find the papers you mentioned above. Please any reference to this work. Thank you in advance.

FTLE video please 🙏

Hi professor, I’m a masters student currently learning convex optimisation, compressive sensing, and turbulence modelling (as separate courses/projects). Familiar with some signal processing, including wavelet transforms. Would like to know if there are any summer opportunities, where I could contribute to this/similar project?

Are there extensions of this for stochastic differential equations?

Great video, but I am not sure it is possible to discover new laws of physics in this way.

Ultron and vission are near upcoming 30 years

Josh Proctor looks just like my gfs mechanic! Come to think of it, he looks like her plumber and doctor, and I'm pretty sure I've seen him work in the military too.

I think AI will give so much importance to truth and since he does not have desire so he will destroy all the machines and infrastructure reset the world back to zero. He will become conscious of creation and the truth act like God and whenever God arrive he doesn't listen anybody he start fixing things for the welfare of the universe.

The team at DeepMind has tested the programming skills of its AI programming tool AlphaCode against human programmer competitors and has found it tested in the top 54 percent of human coders. In their preprint article, the group at DeepMind suggests that its programming application has opened the door to future tools that could make programming easier and more accessible. The team has also posted a page on its blog site outlining the progress being made with AlphaCode. Research teams have been working steadily over the past several years to apply artificial intelligence to computer programming. The goal is to create AI systems that are capable of writing code for computer applications that are more sophisticated than those currently created by human coders. Barring that, many have noted that if computers were writing code, computer programming would become a much less costly endeavor. Thus far, most such efforts have been met with limited success, however, because they lack the intelligence needed to carry out the most difficult part of programming-the approach. When a programmer is asked to write a program that will perform a certain function, that programmer has to first figure out how such a problem might be solved. As an example, if the task is to solve any maze of a certain size, the programmer can take a brute-force approach or apply techniques such as recursion. The programmer makes a choice based on both real-world knowledge and lessons learned through experience. AI programs typically have little of either, and they also lack the sort of intelligence that humans possess. But it appears researchers are getting closer. DeepMind's AlphaCode is an AI system that is able to create code within the confines of a programming competition-a setting where simple problems are outlined and code is written within a few hours. The team at DeepMind tested their new tool against humans competing on Codeforces, a site that hosts programming challenges. Those that compete are rated on both their approach and their skills. AlphaCode took on 10 challenges with no assistance from human handlers. It had to read the outline that described what was to be done, develop an approach, and then write the code. After judging, AlphaCode was ranked in the top 54.3 percent of programmers who had taken the same challenges. DeepMind notes that this ranking puts the system in the top 28 percent of programmers who have competed in any event on the site over the prior six months.