Klaus Thoeni
Civil and Structural Engineering · 2016–2019
A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Civil and Structural Engineering — 16 citations into it
- Computational Mechanics — 11 citations into it
- Management, Monitoring, Policy and Law — 9 citations into it
- Mechanics of Materials — 8 citations into it
- Artificial Intelligence — 5 citations into it
- Statistics and Probability — 5 citations into it
Whom Klaus Thoeni trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Klaus Thoeni's perspective
Ordered by how strongly the researchers Klaus Thoeni trusts endorse each paper. Same corpus, a different order for every researcher.
- Pattern Recognition and Machine Learning
- Scikit-learn: Machine Learning in Python
- Variational inference for Dirichlet process mixtures
- Application of experimental design and optimization to PFC model calibration in uniaxial compression simulation
- The Infinite Gaussian Mixture Model
- Numerical simulation of drained triaxial test using 3D discrete element modeling
- Bayesian Filtering and Smoothing
- A novel discrete model for granular material incorporating rolling resistance
- Bayesian uncertainty quantification and propagation in molecular dynamics simulations: a high performance computing framework.
- A spherical discrete element model: calibration procedure and incremental response
Their papers
- An iterative Bayesian filtering framework for fast and automated calibration of DEM models (2019) — 102 citations
- Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter (2018) — 64 citations
- Modelling of deformable structures in the general framework of the discrete element method (2016) — 72 citations