Francesco Pinto

Francesco Pinto

Francesco Pinto, DPhil Student, University of Oxford, TVG. Specialization areas: probabilistic programming, bayesian deep learning, uncertainty estimation.

Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks

Published in DistShift, NeurIPS 2021 Workshop, 2021

Recommended citation: Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H.S. Torr, Puneet K. Dokania (2021). "Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks." NeurIPS 2021: DistShift, 2021 https://openreview.net/pdf?id=hlVgM8XcssV

Download paper here

Recommended citation: Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H.S. Torr, Puneet K. Dokania (2021). “Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks.” NeurIPS 2021: DistShift, 2021.

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