dida contributes paper to ICML 2023

We are happy to announce that the paper „Improved sampling via learned diffusions“ has been accepted at the workshop „New Frontiers in Learning, Control, and Dynamical Systems“ which takes place at the International Conference on Machine Learning (ICML) this week in Hawaii.

The paper investigates how sampling from specified probability densities can be approached via diffusion processes in which the drift is learned via neural networks. A perspective from measures on path space is proposed which allows to generalize existing concepts such as Schrödinger bridges or diffusion based generative modeling. This new perspective in consequence allows to design more efficient loss functions that can lead to vast improvements in numerical experiments.

At dida, we are very happy that we can continue our ambition to conduct cutting edge research and contribute to the machine learning community. We can therefore continue our path to combine practical machine learning with innovative research. It is the company’s philosophy that both worlds strongly benefit from one another.