Scope of Submission
We welcome submissions from a broad range of disciplines, including but not limited to:
- Data-driven approaches in numerical methods
- Machine learning applications in numerical analysis
- Numerical methods for big data problems
- Adaptive algorithms for data-driven simulations
- Statistical methods in numerical modeling
- Data assimilation techniques in numerical methods
- Numerical optimization using data-driven techniques
- Uncertainty quantification in data-driven models
- High-dimensional data and numerical methods
- Parallel computing for data-driven simulations
- Real-time data processing in numerical analysis
- Data-driven error analysis in numerical methods
- Numerical methods for nonlinear data-driven problems
- Integration of AI in numerical simulations
- Data-driven approaches to PDEs
- Visualization techniques for numerical data
- Data-driven model reduction techniques
- Numerical methods for dynamic data sets
- Applications of data-driven methods in engineering
- Future trends in data-driven numerical methods
All papers must be original and not previously published or submitted elsewhere.
