T. Shuku

Civil and Structural Engineering · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom T. Shuku trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. C. Coetzee
  2. J. Yoon
  3. Michael I. Jordan
  4. Simo Särkkä
  5. M. Rackl
  6. Ignacio Arganda-Carreras
  7. Costas Papadimitriou

Papers from T. Shuku's perspective

Ordered by how strongly the researchers T. Shuku trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Pattern Recognition and Machine Learning
  2. Scikit-learn: Machine Learning in Python
  3. Variational inference for Dirichlet process mixtures
  4. Application of experimental design and optimization to PFC model calibration in uniaxial compression simulation
  5. The Infinite Gaussian Mixture Model
  6. Numerical simulation of drained triaxial test using 3D discrete element modeling
  7. Bayesian Filtering and Smoothing
  8. A novel discrete model for granular material incorporating rolling resistance
  9. Bayesian uncertainty quantification and propagation in molecular dynamics simulations: a high performance computing framework.
  10. A spherical discrete element model: calibration procedure and incremental response

Their papers