Ziniu Hu's Website
Keyan Miao
Description: Website for workshop
In the deep learning community, a remarkable trend is emerging, where powerful architectures are created by leveraging classical mathematical modeling tools from diverse fields like differential equations, signal processing, and dynamical systems. Differential equations are a prime example: research on neural differential equations has expanded to include a large zoo of related models with applications ranging from time series analysis to robotics control. Score-based diffusion models are among state-of-the
The previous two editions of the Workshop on the Symbiosis of Deep Learning and Differential Equations have promoted the bidirectional exchange of ideas at the intersection of classical mathematical modelling and modern deep learning. On the one hand, this includes the use of differential equations and similar tools to create neural architectures, accelerate deep learning optimization problems, or study theoretical problems in deep learning. On the other hand, the Workshop also explores the use of deep lear
We invite high-quality extended abstract submissions on the intersection of DEs and DL, including but not limited to works that connect to this year's focus area of neural architectures that leverage classical mathematical models (see above). Some examples (non-exhaustive list):
Ziniu Hu's Website
Keyan Miao