Kaj Nyström

13 papers B 1Journal 12
YearRankTypeTitle / Venue / Authors
2022 J jnl
Deep learning, stochastic gradient descent and diffusion maps.
CoRR
Carmina Fjellström, Kaj Nyström
2022 J jnl
Hawkes-based models for high frequency financial data.
J. Oper. Res. Soc.
Kaj Nyström, Changyong Zhang
2021 J jnl
Solving the Dirichlet problem for the Monge-Ampère equation using neural networks.
CoRR
Kaj Nyström, Matias Vestberg
2019 J jnl
Data-driven discovery of PDEs in complex datasets.
J. Comput. Phys.
Jens Berg, Kaj Nyström
2019 J jnl
Neural ODEs as the Deep Limit of ResNets with constant weights.
CoRR
Benny Avelin, Kaj Nyström
2018 J jnl
A unified deep artificial neural network approach to partial differential equations in complex geometries.
Neurocomputing
Jens Berg, Kaj Nyström
2018 J jnl
Data-driven discovery of PDEs in complex datasets.
CoRR
Jens Berg, Kaj Nyström
2017 J jnl
A unified deep artificial neural network approach to partial differential equations in complex geometries.
CoRR
Jens Berg, Kaj Nyström
2015 J jnl
Optimal switching problems under partial information.
Monte Carlo Methods Appl.
Kai Li, Kaj Nyström, Marcus Olofsson
2010 J jnl
Adaptive stochastic weak approximation of degenerate parabolic equations of Kolmogorov type.
J. Comput. Appl. Math.
Marie Frentz, Kaj Nyström
2010 J jnl
Pricing and hedging of financial derivatives using a posteriori error estimates and adaptive methods for stochastic differential equations.
J. Comput. Appl. Math.
Kaj Nyström, Thomas Önskog
2009 J jnl
On Monte Carlo algorithms applied to Dirichlet problems for parabolic operators in the setting of time-dependent domains.
Monte Carlo Methods Appl.
Kaj Nyström, Thomas Önskog
2006 B conf
Determining over- and under-constrained systems of equations using structural constraint delta.
GPCE
David Broman, Kaj Nyström, Peter Fritzson