Van Kien Nguyen

25 papers Journal 21Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Approximation of PDE solution manifolds: Sparse-grid interpolation and quadrature. CoRR Dinh Dung, Van Kien Nguyen, Duong Thanh Pham, Christoph Schwab
2026	J	`jnl`	Elliptic PDEs on log-Gaussian Shapes: Sparsity and Finite Element Discretization. CoRR Dinh Dung, Helmut Harbrecht, Van Kien Nguyen, Christoph Schwab
2026	J	`jnl`	Sparsity for parametric PDEs with log-gamma random inputs and applications. CoRR Dinh Dung, Van Kien Nguyen, Viet Ha Hoang
2025	J	`jnl`	Pseudo s-numbers of embeddings of Gaussian weighted Sobolev spaces. J. Approx. Theory Van Kien Nguyen
2023	J	`jnl`	Deep ReLU neural network approximation in Bochner spaces and applications to parametric PDEs. J. Complex. Dinh Dung, Van Kien Nguyen, Duong Thanh Pham
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`	Analyticity of Parametric and Stochastic Elliptic Eigenvalue Problems with an Application to Quasi-Monte Carlo Methods. CoRR Van Kien Nguyen
2022	J	`jnl`	Optimal numerical integration and approximation of functions on R CoRR Dinh Dung, Van Kien Nguyen
2022	J	`jnl`	s-Numbers of embeddings of weighted Wiener algebras. J. Approx. Theory Van Dung Nguyen, Van Kien Nguyen, Winfried Sickel
2021	J	`jnl`	Computation complexity of deep ReLU neural networks in high-dimensional approximation. CoRR Dinh Dung, Van Kien Nguyen, Mai Xuan Thao
2021	J	`jnl`	Deep ReLU neural network approximation of parametric and stochastic elliptic PDEs with lognormal inputs. CoRR Dinh Dung, Van Kien Nguyen, Duong Thanh Pham
2021	J	`jnl`	Deep ReLU neural networks in high-dimensional approximation. Neural Networks Dinh Dung, Van Kien Nguyen
2021	J	`jnl`	High-dimensional nonlinear approximation by parametric manifolds in Hölder-Nikol'skii spaces of mixed smoothness. CoRR Dinh Dung, Van Kien Nguyen
2020	J	`jnl`	Greedy algorithms and Kolmogorov widths in Banach spaces. J. Approx. Theory Van Kien Nguyen
2020	J	`jnl`	Sparse-grid sampling recovery and deep ReLU neural networks in high-dimensional approximation. CoRR Dinh Dung, Van Kien Nguyen
2020	J	`jnl`	Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances. SIAM J. Numer. Anal. Markus Bachmayr, Ivan G. Graham, Van Kien Nguyen, Robert Scheichl
2018	J	`jnl`	Monte Carlo methods for uniform approximation on periodic Sobolev spaces with mixed smoothness. J. Complex. Glenn Byrenheid, Robert J. Kunsch, Van Kien Nguyen
2017	J	`jnl`	94-GHz CMOS Power Amplifiers Using Miniature Dual Y-Shaped Combiner With RL Load. IEEE Trans. Circuits Syst. I Regul. Pap. Yo-Sheng Lin, Van Kien Nguyen
2017	J	`jnl`	Gelfand numbers of embeddings of mixed Besov spaces. J. Complex. Van Kien Nguyen
2016	—	`conf`	A 7.2 mW 74∼82 GHz CMOS low-noise amplifier with 17.3±1.5 dB gain and 7.7±0.3 dB NF for automotive radar systems. RWS Yo-Sheng Lin, Van Kien Nguyen, Hsin-Chen Lin, Chien-Yo Lee, Chien-Chin Wang, Chih-Chung Chen, Yun-Wen Lin
2016	—	`conf`	A low noise figure and high conversion gain down-conversion mixer for 94 GHz image radar sensors in 90 nm CMOS. RWS Yo-Sheng Lin, Chih-Chung Chen, Jay-Ming Liu, Yun-Wen Lin, Van Kien Nguyen
2016	—	`conf`	A wideband power amplifier with 13.2 dBm Psat and 19.5% PAE for 60∼94 GHz wireless communication systems in 90 nm CMOS. RWS Yo-Sheng Lin, Van Kien Nguyen, Jia-Wei Gao, Chien-Chin Wang, Yun-Wen Lin, Chih-Chung Chen
2016	—	`conf`	Design and implementation of a high-performance CMOS dual balun for millimeter-wave star mixer and four-way power amplifier. RWS Yo-Sheng Lin, Yun-Wen Lin, Chien-Chin Wang, Chih-Chung Chen, Van Kien Nguyen
2016	J	`jnl`	Weyl and Bernstein numbers of embeddings of Sobolev spaces with dominating mixed smoothness. J. Complex. Van Kien Nguyen
2015	J	`jnl`	Weyl numbers of embeddings of tensor product Besov spaces. J. Approx. Theory Van Kien Nguyen, Winfried Sickel