Call for Abstracts

The Deep Learning revolution over the last decade has progressively invaded all fields of digital science and is gradually establishing itself as a complement to physical sciences at all stages of modeling, simulation, optimization and control of complex systems.
Following the successful first edition in 2021, and second edition in 2022 starting as an echo of the IA2 Program at IRT SystemX, the third workshop, co-organized with Systematic and the DATAIA Institute, will feature two international keynote presentations, and will allow researchers to present their most recent works.

Contributed presentations are solicited, covering various topics in the field, including but not limited to the following:

• Handling and explaining the massive output data of heavy numerical simulations
• Accelerating numerical simulations with Deep / Machine Learning
• Improving the accuracy or the robustness of simulations with Machine Learning
• Learning to solve ODEs and PDEs
• Discovering mechanistic/behavioral models from data
• Incorporating physical constraints in Deep Learning
• Providing support in augmented decision making for complex systems
• Knowledge extraction and reasoning techniques from heterogeneous data

You are invited to submit an abstract (up to 2 pages).

Extended Abstract submission deadline: November 6th 16th 2023