Neural Modeling and Differential Equations | Isaac Elias Lagaris, University of Ioannina (Greece)


Friday, April 12, 2019, 1:30pm to 2:30pm


Harvard University, Maxwell Dworkin G115, 33 Oxford Street, Cambridge, MA 02138

This talk will begin promptly at 1:30pm. 

Abstract: The universal approximation capability of neural networks is exploited to recover solutions of Differential Equations.  The process of solving a Differential Equation is reduced to that of training a Neural Form.  Boundary conditions may be satisfied either by proper construction of the neural form, or alternatively, by treating them as constraints.

Bio: Isaac E. Lagaris

  • Current Position: Professor, Department of Computer Science & Engineering, University of Ioannina
  • Education: B.Sc. in Physics (1975), University of Ioannina (Ioannina, Greece)
  • M.Sc. in Physics (1977) & Ph.D. in Physics (1981), University of Illinois (Champaign-Urbana, USA)
  • Visiting Scientist at:
  • University of Pisa, University of Lecce (Italy)
  • University of South Africa, University of the Witwatersrand (S. Africa)
  • COURANT Institute - New York University, Nuclear Engineering - Purdue University (USA)
  • Scientific Interests:
  • Local and Global optimization, Modeling & Simulation, Neural Networks, Pattern Recognition.

**This event is free and open to the public; no registration required.**

See also: Seminar