Paul Novello

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 14

Top Topics

Top Venues

J. Comput. Phys.

Publications

Paul Novello, Joseba Dalmau, Léo Andéol
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?). CoRR (2024)
Paul Novello, Yannick Prudent, Joseba Dalmau, Corentin Friedrich, Yann Pequignot
Improving Out-of-Distribution Detection by Combining Existing Post-hoc Methods. CoRR (2024)
Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). J. Comput. Phys. 498 (2024)
Louis Béthune, Paul Novello, Guillaume Coiffier, Thibaut Boissin, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. ICML (2023)
Louis Béthune, Paul Novello, Thibaut Boissin, Guillaume Coiffier, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. CoRR (2023)
Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Lore Goetschalckx, Laurent Gardes, Thomas Serre
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. NeurIPS (2023)
Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Laurent Gardes, Thomas Serre
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. CoRR (2023)
Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot, Paul Novello, Liam Paull
GROOD: GRadient-aware Out-Of-Distribution detection in interpolated manifolds. CoRR (2023)
Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo
Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. J. Sci. Comput. 94 (3) (2023)
Paul Novello, Thomas Fel, David Vigouroux
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. CoRR (2022)
Paul Novello, Thomas Fel, David Vigouroux
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. NeurIPS (2022)
Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo
Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. CoRR (2022)
Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). CoRR (2022)
Paul Novello, Gaël Poëtte, David Lugato, Pietro Congedo
Variance Based Samples Weighting for Supervised Deep Learning. CoRR (2021)