Data Management, Model Reduction, Deep Neural Nets

  • H. Antil, T.S. Brown, R. Löhner, F. Togashi and D. Veerma – Deep Neural Nets with Fixed Bias Configuration; arXiv:2107.01308 [math.OC] (2021).
  • T. Brown, H. Antil, R. Löhner, F. Togashi and D. Verma – Novel DNNS for Stiff ODEs With Applications to Chemically Reacting Flows; {\sl CFDML2021: 2nd Int.\ Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis }, Held in conjunction with the International Supercomputing Conference (ISC) High Performance 2021, July 2 (2021). arXiv:2104.01914v1 [cs.LG] (2021).
  • R. Löhner, H. Antil, H.R. Tamaddon-Jahromi, N.K. Chakshu and P. Nithiarasu – Deep Learning or Interpolation for Inverse Modelling of Heat and Fluid Flow Problems ?; Int. J. Num. Meth. Heat and Fluid Flow (2020)
  • H. Antil, R. Khatri, R. Löhner and D. Verma – Fractional Deep Neural Network Via Constrained Optimization; arXiv:2004.00719 math.OC. Mach. Learn.: Sci. Technol. 2, 1 015003