Simon Scheidegger
Simon Scheidegger
Department of Economics, Faculty of Business and Economics (HEC Lausanne), University of Lausanne
Verified email at - Homepage
Cited by
Cited by
Using adaptive sparse grids to solve high‐dimensional dynamic models
J Brumm, S Scheidegger
Econometrica 85 (5), 1575-1612, 2017
The influence of model parameters on the prediction of gravitational wave signals from stellar core collapse
S Scheidegger, R Käppeli, SC Whitehouse, T Fischer, M Liebendörfer
Astronomy & Astrophysics 514, A51, 2010
Large-scale sparse inverse covariance matrix estimation
M Bollhöfer, A Eftekhari, S Scheidegger, O Schenk
SIAM Journal on Scientific Computing 41 (1), A380-A401, 2019
Gravitational waves from 3D MHD core collapse simulations
S Scheidegger, T Fischer, S Whitehouse, L Matthias
Astronomy & Astrophysics, 0
Deep Equilibrium Nets
M Azinovic, L Gaegauf, S Scheidegger, 0
Machine learning for high-dimensional dynamic stochastic economies
S Scheidegger, I Bilionis
Journal of Computational Science 33, 68-82, 2019
Making Carbon Taxation a Generational Win Win
LJ Kotlikoff, F Kubler, A Polbin, JD Sachs, S Scheidegger
NBER Working Paper No. 25760, 2019
FISH: a three-dimensional parallel magnetohydrodynamics code for astrophysical applications
R Käppeli, SC Whitehouse, S Scheidegger, UL Pen, M Liebendörfer
The Astrophysical Journal Supplement Series 195 (2), 20, 2011
Gravitational waves from supernova matter
S Scheidegger, SC Whitehouse, R Käppeli, M Liebendörfer
Classical and Quantum Gravity 27 (11), 114101, 2010
Can today's and tomorrow's world uniformly gain from carbon taxation?
LJ Kotlikoff, F Kubler, A Polbin, S Scheidegger
National Bureau of Economic Research, 2021
The climate in climate economics
D Folini, A Friedl, F Kübler, S Scheidegger
Review of Economic Studies, rdae011, 2024
Scalable high-dimensional dynamic stochastic economic modeling
J Brumm, D Mikushin, S Scheidegger, O Schenk
Journal of Computational Science 11, 12-25, 2015
Computing equilibria in dynamic stochastic macro-models with heterogeneous agents
J Brumm, F Kubler, S Scheidegger
Advances in economics and econometrics 2, 185, 2017
Pareto-improving carbon-risk taxation
L Kotlikoff, F Kubler, A Polbin, S Scheidegger
Economic Policy 36 (107), 551-589, 2021
Machine Learning for Dynamic Incentive Problems
P Renner, S Scheidegger, 2018
Sparse grids for dynamic economic models
J Brumm, C Krause, A Schaab, S Scheidegger
Available at SSRN 3979412, 2021
Deep structural estimation: With an application to option pricing
H Chen, A Didisheim, S Scheidegger
arXiv preprint arXiv:2102.09209, 2021
Rethinking large-scale economic modeling for efficiency: Optimizations for gpu and xeon phi clusters
S Scheidegger, D Mikushin, F Kubler, O Schenk
2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2018
Self-justified equilibria: Existence and computation
F Kubler, S Scheidegger
Available at SSRN 3494876, 2019
Pricing American Options under High-Dimensional Models with Recursive Adaptive Sparse Expectations
S Scheidegger, A Treccani
Journal of Financial Econometrics, 2018
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