Cita APA (7th ed.)

Venturini, L., Papageorghiou, A., Noble, J., & Namburete, A. (2020). Uncertainty estimates as data selection criteria to boost omni-supervised learning. Springer Nature.

Cita Chicago (17th ed.)

Venturini, L., AT Papageorghiou, JA Noble, i AIL Namburete. Uncertainty Estimates as Data Selection Criteria to Boost Omni-supervised Learning. Springer Nature, 2020.

Cita MLA (9th ed.)

Venturini, L., et al. Uncertainty Estimates as Data Selection Criteria to Boost Omni-supervised Learning. Springer Nature, 2020.