Bridging the gap between Numerical analysis and Physics-informed Machine Learning: Stability and Theoretical Convergence for Stiff ODEs and PDEs
Talk, DDE24, Bremen, Germany
Talks and presentations
Physics-Informed Random Projection Neural Networks for the numerical solution of stiff ODEs, DAEs and PDEs
Talk, SIAM UQ24, Trieste, Italy
Tipping Points via Machine Learning: Comparing Data-driven Global PDE and Local SDE surrogates
Talk, CCS/Italy 2023, Naples, Italy
Parsimonious Physics-Informed Random Projection Neural Networks (PIRPNN) for initial value problems of ODEs, index-1 DAEs and PDEs
Talk, Dynamics Days Europe 2023, Naples, Italy
Parsimonious Physics-Informed Random Projection Neural Networks (PIRPNN) for solving Forward and Inverse Problems
Talk, Crunch Seminars, Brown, Division of Applied Mathematics
Youtube video
here the following video of the talk (presentation #2) https://www.youtube.com/watch?v=eEiN3bN1TxE&t=134s
Numerical Solution of stiff ODEs, DAEs with adaptive Physics-Informed Random Projection Neural Networks
Talk, NUMTA DS23, Pizzo Calabro (VV), Italy
Constructing Integro-PDEs for the Emergent Dynamics of Agent-Based Simulations: A Machine Learning Approach
Talk, SIAM DS23, Portland, Oregon, USA
Machine Learning-based coarse-scale Identification and bifurcation analysis for modelling Tipping Points: a financial market Agent-Based illustration
Talk, AAAI Spring Symposium Series, Palo Alto, California
Identifying the emergent dynamics of Agent Based Models: Coarse-scale Integro-PDEs from fine scale simulations
Talk, 2022 Conference in Nonlinear Science and Complexity, Thessaloniki, Greece