Categories |
MACHINE LEARNING
DIFFERENTIAL EQUATIONS
DEEP LEARNING
|
About |
|
Differential equations form the bedrock of scientific computing, while neural networks have emerged as the preferred tool of modern machine learning. These two methods are not only closely related to each other but also offer complementary strengths: the modelling power and interpretability of differential equations, and the approximation and generalization power of deep neural networks. While progress has been made on combining differential equations and deep neural networks, most existing work has been disjointed, and a coherent picture has yet to emerge. Thus, a theoretical foundation for integrating deep neural networks and differential equations remains poorly understood, with many more questions than answers. For example: How can we incorporate a given ordinary/partial differential equation (ODE/PDE) into an architecture of a deep neural network? Under what assumptions can we approximate a system of ODEs/PDEs by deep neural networks? How good are these approximations? How can we interpret deep neural networks from the perspective of ODEs/PDEs? How well-developed mathematical tools for ODEs/PDEs can be leveraged to help us gain a better understanding of deep neural networks and improve their performance? Substantive progress will require a principled approach that integrates ideas from the disparate lens, including differential equations, machine learning, numerical analysis, optimization, optimal transport, computer graphics, and physics. |
Call for Papers |
|
The goal of this workshop is to provide a forum where theoretical and experimental researchers of all stripes can come together not only to share reports on their progress but also to find new ways to join forces towards the goal of coherent integration of deep neural networks and differential equations. Topics to be discussed include, but are not limited to:
|
Summary |
|
DEEPDIFFEQ 2020 : ICLR Workshop on Integration of Deep Neural Models and Differential Equations will take place in Addis Ababa, Ethiopia. It’s a 1 day event starting on Apr 26, 2020 (Sunday) and will be winded up on Apr 26, 2020 (Sunday). DEEPDIFFEQ 2020 falls under the following areas: MACHINE LEARNING, DIFFERENTIAL EQUATIONS, DEEP LEARNING, etc. Submissions for this Workshop can be made by Feb 18, 2020. Authors can expect the result of submission by Feb 25, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Apr 19, 2020 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the DEEPDIFFEQ 2020
|
Credits and Sources |
| [1] DEEPDIFFEQ 2020 : ICLR Workshop on Integration of Deep Neural Models and Differential Equations |
