We are happy to announce that dida will contribute a paper and a long presentation to this year’s International Conference on Machine Learning (ICML), which is one of the most popular conferences on artificial intelligence worldwide. Out of 5513 submissions only 166 (i.e. roughly 3%) got offered this opportunity. Our paper suggests an efficient numerical solver for high-dimensional parabolic partial differential equations, which are relevant for example in engineering, physics and finance. It relies on the tensor train format and contrasts this approach to deep neural networks as an alternative method. You can find a preprint version here.
After a paper at last year’s NeurIPS conference, for which you can find a short video presentation, we are pleased that we can continue to foster our ambition to combine practical machine learning with cutting edge research. It is the company’s philosophy that both worlds can strongly benefit from one another.
If you have any questions regarding the papers or other topics, please do not hesitate to contact us.