Preprints
T. DeRyck, S. Mishra and D. Ray, On the approximation of rough functions with deep neural networks, Preprint 2020, external pagearXiv:1912.06732call_made.
S. Mishra and R. Molinaro, Estimates on the generalization error of Physics informed neural networks (PINNs) for approximating PDEs, Preprint 2020, external pagearXiv:2006.16144call_made.
S. Lanthaler, S. Mishra and G. E. Karniadakis, Error estimates for DeepOnets: A deep learning framework in infinite dimensions, Preprint 2021. external pagearXiv:2102.09618call_made.
T. De Ryck and S. Mishra, Error analysis for physics informed neural networks (PINNs) approximating Kolmogorov PDEs, Preprint 2021, external pagearXiv:2106.14473call_made.
N. Kovachki, S. Lanthaler and S. Mishra, On universal approximation and error bounds for Fourier Neural Operators, Preprint 2021, external pagearXiv:2107.07562call_made.
S. Lanthaler, S. Mishra and F. Weber, On the well-posedness of Bayesian inversion for PDEs with ill-posed forward problems, Preprint 2021, external pagearXiv:2107.07593call_made.
S. Mishra, D. Ochsner, A. M. Ruf and F. Weber, Well-posedness of Bayesian inverse problems for hyperbolic conservation laws, Preprint 2021, external pagearXiv:2107.09701call_made.
T. K. Rusch, S. Mishra, N. B. Erichson and M. Mahoney, Long Expressive Memory for sequence modeling, Preprint 2021, external pagearXiv:04744call_made.
U. S. Fjordholm, S. Mishra and F. Weber, On the vanishing viscosity limit of statistical solutions of the incompressible Navier-Stokes equations, Preprint 2021, external pagearXiv:2110.04674call_made.
T. K. Rusch, B. P. Chamberlain, J. Rowbottom, S. Mishra and M. M. Bronstein, Graph Coupled Oscillator Networks, Preprint 2022, external pagearXiv:2202.02296v1call_made