Daniel Wälchli

发表

Korali: Efficient and scalable software framework for Bayesian uncertainty quantification and stochastic optimization

Petros Koumoutsakos, Georgios Arampatzis, Daniel Wälchli, 2020, Computer Methods in Applied Mechanics and Engineering.

Optimal Allocation of Limited Test Resources for the Quantification of COVID-19 Infections

M. Chatzimanolakis, P. Weber, G. Arampatzis, 2020, medRxiv.

Data-driven inference of the reproduction number for COVID-19 before and after interventions for 51 European countries.

P. Koumoutsakos, C. Papadimitriou, F. Wermelinger, 2020, Swiss medical weekly.

Load Balancing in Large Scale Bayesian Inference

Sergio M. Martin, P. Koumoutsakos, X. Bian, 2020, PASC.

Korali: a High-Performance Computing Framework for Stochastic Optimization and Bayesian Uncertainty Quantification pdf

Petros Koumoutsakos, Sergio M. Martin, Georgios Arampatzis, 2020, ArXiv.

Remember and Forget Experience Replay for Multi-Agent Reinforcement Learning

P. Koumoutsakos, D. Wälchli, Pascal Weber, 2022, ArXiv.

Optimal allocation of limited test resources for the quantification of COVID-19 infections.

P. Koumoutsakos, C. Papadimitriou, P. Karnakov, 2020, Swiss medical weekly.

Optimal Testing Strategy for the Identification of COVID-19 Infections

C. Papadimitriou, M. Chatzimanolakis, P. Weber, 2020, medRxiv.

(μ,λ)-CCMA-ES for Constrained Optimization with an Application in Pharmacodynamics

Petros Koumoutsakos, Pascal Weber, Georgios Arampatzis, 2019, PASC.

Langevin Diffusion for Population Based Sampling with an Application in Bayesian Inference for Pharmacodynamics

Panagiotis Angelikopoulos, Petros Koumoutsakos, Stephen Wu, 2016, SIAM J. Sci. Comput..

Langevin Diffusion Transitional Markov Chain Monte Carlo with an Application to Pharmacodynamics

P. Koumoutsakos, G. Arampatzis, Stephen Wu, 2016 .

Data driven inference of the reproduction number (R0) for COVID-19 before and after interventions for 51 European countries

C. Papadimitriou, G. Arampatzis, I. Kicic, 2020, medRxiv.