Jakob Zech - RankMe

32 papers A* 2Journal 30

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adaptive Kernel Selection for Stein Variational Gradient Descent. CoRR Moritz Melcher, Simon Weissmann, Ashia C. Wilson, Jakob Zech
2025	J	`jnl`	Distribution learning via neural differential equations: minimal energy regularization and approximation theory. CoRR Youssef M. Marzouk, Zhi Ren, Jakob Zech
2025	J	`jnl`	Low Stein Discrepancy via Message-Passing Monte Carlo. CoRR Nathan Kirk, T. Konstantin Rusch, Jakob Zech, Daniela Rus
2025	J	`jnl`	Metropolis-adjusted interacting particle sampling. Stat. Comput. Björn Sprungk, Simon Weissmann, Jakob Zech
2025	A*	`conf`	Optimal Scheduling of Dynamic Transport. COLT Panos Tsimpos, Zhi Ren, Jakob Zech, Youssef Marzouk
2025	J	`jnl`	Optimal Scheduling of Dynamic Transport. CoRR Panos Tsimpos, Zhi Ren, Jakob Zech, Youssef Marzouk
2025	J	`jnl`	Quantum Circuit Encodings of Polynomial Chaos Expansions. CoRR Junaid Aftab, Christoph Schwab, Haizhao Yang, Jakob Zech
2025	J	`jnl`	Sparsity for Infinite-Parametric Holomorphic Functions on Gaussian Spaces. CoRR Carlo Marcati, Christoph Schwab, Jakob Zech
2024	J	`jnl`	Distribution Learning via Neural Differential Equations: A Nonparametric Statistical Perspective. J. Mach. Learn. Res. Youssef M. Marzouk, Zhi (Robert) Ren, Sven Wang, Jakob Zech
2024	J	`jnl`	Mathematical theory of deep learning. CoRR Philipp Petersen, Jakob Zech
2024	J	`jnl`	Neural and spectral operator surrogates: unified construction and expression rate bounds. Adv. Comput. Math. Lukas Herrmann, Christoph Schwab, Jakob Zech
2024	J	`jnl`	On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation. CoRR Simon Weissmann, Jakob Zech
2024	J	`jnl`	Statistical Learning Theory for Neural Operators. CoRR Niklas Reinhardt, Sven Wang, Jakob Zech
2023	J	`jnl`	De Rham compatible Deep Neural Network FEM. Neural Networks Marcello Longo, Joost A. A. Opschoor, Nico Disch, Christoph Schwab, Jakob Zech
2023	J	`jnl`	Deep Learning in High Dimension: Neural Network Expression Rates for Analytic Functions in \(\pmb{L^2(\mathbb{R}^d,\gamma_d)}\). SIAM/ASA J. Uncertain. Quantification Christoph Schwab, Jakob Zech
2023	J	`jnl`	Deep Operator Network Approximation Rates for Lipschitz Operators. CoRR Christoph Schwab, Andreas Stein, Jakob Zech
2023	J	`jnl`	Distribution learning via neural differential equations: a nonparametric statistical perspective. CoRR Youssef M. Marzouk, Zhi Ren, Sven Wang, Jakob Zech
2023	J	`jnl`	Measure transport via polynomial density surrogates. CoRR Josephine Westermann, Jakob Zech
2023	J	`jnl`	Metropolis-adjusted interacting particle sampling. CoRR Björn Sprungk, Simon Weissmann, Jakob Zech
2022	J	`jnl`	Analyticity and sparsity in uncertainty quantification for PDEs with Gaussian random field inputs. CoRR Dinh Dung, Van Kien Nguyen, Christoph Schwab, Jakob Zech
2022	J	`jnl`	De Rham compatible Deep Neural Networks. CoRR Marcello Longo, Joost A. A. Opschoor, Nico Disch, Christoph Schwab, Jakob Zech
2022	J	`jnl`	Multilevel Domain Uncertainty Quantification in Computational Electromagnetics. CoRR Rubén Aylwin, Carlos Jerez-Hanckes, Christoph Schwab, Jakob Zech
2022	A*	`conf`	Multilevel Optimization for Inverse Problems. COLT Simon Weissmann, Ashia Wilson, Jakob Zech
2022	J	`jnl`	Multilevel Optimization for Inverse Problems. CoRR Simon Weissmann, Ashia Wilson, Jakob Zech
2022	J	`jnl`	Neural and gpc operator surrogates: construction and expression rate bounds. CoRR Lukas Herrmann, Christoph Schwab, Jakob Zech
2021	J	`jnl`	Deep Learning in High Dimension: Neural Network Approximation of Analytic Functions in L CoRR Christoph Schwab, Jakob Zech
2021	J	`jnl`	Sparse approximation of triangular transports. Part II: the infinite dimensional case. CoRR Jakob Zech, Youssef M. Marzouk
2020	J	`jnl`	Domain Uncertainty Quantification in Computational Electromagnetics. SIAM/ASA J. Uncertain. Quantification Rubén Aylwin, Carlos Jerez-Hanckes, Christoph Schwab, Jakob Zech
2020	J	`jnl`	Sparse approximation of triangular transports on bounded domains. CoRR Jakob Zech, Youssef M. Marzouk
2019	J	`jnl`	Uncertainty Quantification for Spectral Fractional Diffusion: Sparsity Analysis of Parametric Solutions. SIAM/ASA J. Uncertain. Quantification Lukas Herrmann, Christoph Schwab, Jakob Zech
2018	J	`jnl`	Shape Holomorphy of the Stationary Navier-Stokes Equations. SIAM J. Math. Anal. Albert Cohen, Christoph Schwab, Jakob Zech
2015	J	`jnl`	A Posteriori Error Estimation of hp-dG Finite Element Methods for Highly Indefinite Helmholtz Problems. SIAM J. Numer. Anal. Stefan A. Sauter, Jakob Zech