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Selected References
- - Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S.,
+
- Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S.,
& Bloch, I. (2020). Encoding the latent posterior of
Bayesian Neural Networks for uncertainty quantifica-
tion. arXiv preprint arXiv:2012.02818.
- - Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S., &
+
- Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S., &
Bloch, I. (2020). One versus all for deep neural network
incertitude (OVNNI) quantification. IEEE Access
- - Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S., &
+
- Franchi, G., Bursuc, A., Aldea, E., Dubuisson, S., &
Bloch, I. (2020, August). TRADI: Tracking deep neural
network weight distributions. ECCV 2020
- - Franchi, G., Yu, X., Bursuc, A., Aldea, E., Dubuisson,
+
- Franchi, G., Yu, X., Bursuc, A., Aldea, E., Dubuisson,
S., & Filliat, D. (2022, October). Latent Discriminant
deterministic Uncertainty. ECCV 2022
- Laurent, O., Lafage, A., Tartaglione, E., Daniel, G.,
- Martinez, J. M., Bursuc, A., & Franchi, G.
+ Martinez, J. M., Bursuc, A., & Franchi, G.
Packed-Ensembles for Efficient Uncertainty Estimation. ICLR 2023
- Yu, X., Franchi, G., & Aldea, E. (2022, October). On
Monocular Depth Estimation and Uncertainty Quantifi-
@@ -201,304 +198,6 @@
Selected References
-
@@ -508,8 +207,6 @@
Tutorial Schedule
-
-