Simon Scheidegger 个人学术档案

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引用	1083	785
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Felix KublerUniversity of Zurich and Swiss Finance Institute在 bf.uzh.ch 的电子邮件经过验证
Roger KäppeliETH Zurich在 sam.math.ethz.ch 的电子邮件经过验证
Olaf SchenkProfessor, Institute of Computing, Universita della Svizzera italiana, SIAM Fellow在 usi.ch 的电子邮件经过验证
Laurence KotlikoffBoston University在 bu.edu 的电子邮件经过验证
Aryan EftekhariUniversity of Lausanne在 unil.ch 的电子邮件经过验证
Tobias FischerUniversity of Wroclaw在 uwr.edu.pl 的电子邮件经过验证
Polbin AndreyRussian Presidential Academy of National Economy and Public Administration在 ranepa.ru 的电子邮件经过验证
Johannes BrummKarlsruhe Insitute of Technology在 kit.edu 的电子邮件经过验证
Matthias BollhöferProfessor for Numerical Analysis, TU Braunschweig在 tu-bs.de 的电子邮件经过验证
Friedrich-Karl ThielemannProf. of theor. physics em., Univ. of Basel and guest scientist GSI Darmstadt在 unibas.ch 的电子邮件经过验证
Philipp RennerSenior Lecturer, Department of Economics, Lancaster University在 lancaster.ac.uk 的电子邮件经过验证
Dmitry MikushinUniversity of Lausanne在 kernelgen.org 的电子邮件经过验证
Ilias BilionisAssociate Professor, Mechanical Engineering, Purdue University在 purdue.edu 的电子邮件经过验证
Dimosthenis PasadakisPostdoctoral fellow, Università della Svizzera italiana在 usi.ch 的电子邮件经过验证
Ue-Li PenUniversity of Toronto, Canadian Institute of Theoretical Astrophysics在 cita.utoronto.ca 的电子邮件经过验证
Hui ChenProfessor of Finance, MIT在 mit.edu 的电子邮件经过验证
Anthony MezzacappaCollege of Arts and Sciences Excellence Professor and Newton W. and Wilma C. Thomas Chair, UTK在 utk.edu 的电子邮件经过验证
Irina SagertLos Alamos National Laboratory在 lanl.gov 的电子邮件经过验证
Christopher KrauseKarlsruhe Institute of Technology在 kit.edu 的电子邮件经过验证
Andreas SchaabAssistant Professor, Toulouse School of Economics在 tse-fr.eu 的电子邮件经过验证

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Simon Scheidegger

Department of Economics, Faculty of Business and Economics (HEC Lausanne), University of Lausanne

在 unil.ch 的电子邮件经过验证 - 首页

Climate-change economics computational economics machine learning deep learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Using adaptive sparse grids to solve high‐dimensional dynamic models J Brumm, S Scheidegger Econometrica 85 (5), 1575-1612, 2017	174	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	122	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	105	2019
Gravitational waves from 3D MHD core collapse simulations S Scheidegger, T Fischer, S Whitehouse, L Matthias Astronomy & Astrophysics, 0	92*
Deep Equilibrium Nets M Azinovic, L Gaegauf, S Scheidegger https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3393482, 0	91*
Machine learning for high-dimensional dynamic stochastic economies S Scheidegger, I Bilionis Journal of Computational Science 33, 68-82, 2019	75	2019
Making Carbon Taxation a Generational Win Win LJ Kotlikoff, F Kubler, A Polbin, JD Sachs, S Scheidegger NBER Working Paper No. 25760, 2019	58	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	41	2011
Gravitational waves from supernova matter S Scheidegger, SC Whitehouse, R Käppeli, M Liebendörfer Classical and Quantum Gravity 27 (11), 114101, 2010	38	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	27	2021
The climate in climate economics D Folini, A Friedl, F Kübler, S Scheidegger Review of Economic Studies, rdae011, 2024	22	2024
Scalable high-dimensional dynamic stochastic economic modeling J Brumm, D Mikushin, S Scheidegger, O Schenk Journal of Computational Science 11, 12-25, 2015	21	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	20	2017
Pareto-improving carbon-risk taxation L Kotlikoff, F Kubler, A Polbin, S Scheidegger Economic Policy 36 (107), 551-589, 2021	18	2021
Machine Learning for Dynamic Incentive Problems P Renner, S Scheidegger https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3282487, 2018	18	2018
Sparse grids for dynamic economic models J Brumm, C Krause, A Schaab, S Scheidegger Available at SSRN 3979412, 2021	15	2021
Deep structural estimation: With an application to option pricing H Chen, A Didisheim, S Scheidegger arXiv preprint arXiv:2102.09209, 2021	14	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	13	2018
Self-justified equilibria: Existence and computation F Kubler, S Scheidegger Available at SSRN 3494876, 2019	12	2019
Pricing American Options under High-Dimensional Models with Recursive Adaptive Sparse Expectations S Scheidegger, A Treccani Journal of Financial Econometrics, 2018	11	2018

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