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Francesco Locatello
Francesco Locatello
Senior Applied Scientist, Amazon AWS
Potvrđena adresa e-pošte na amazon.com - Početna stranica
Naslov
Citirano
Citirano
Godina
Challenging common assumptions in the unsupervised learning of disentangled representations
F Locatello, S Bauer, M Lucic, G Rätsch, S Gelly, B Schölkopf, O Bachem
ICML 2019 - Proceedings of the 36th International Conference on Machine …, 2019
9772019
Towards Causal Representation Learning
B Schölkopf*, F Locatello*, S Bauer, NR Ke, N Kalchbrenner, A Goyal, ...
Proceedings of the IEEE, 2021
4382021
Object-Centric Learning with Slot Attention
F Locatello*, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ...
NeurIPS 2020 - Thirty-fourth Conference on Neural Information Processing …, 2020
3032020
Weakly-Supervised Disentanglement Without Compromises
F Locatello, B Poole, G Rätsch, B Schölkopf, O Bachem, M Tschannen
ICML 2020 - Proceedings of the 37th International Conference on Machine Learning, 2020
1732020
On the Fairness of Disentangled Representations
F Locatello, G Abbati, T Rainforth, S Bauer, B Schölkopf, O Bachem
NeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, 2019
1592019
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
S van Steenkiste, F Locatello, J Schmidhuber, O Bachem
NeurIPS 2019: Thirty-third Conference on Neural Information Processing Systems, 2019
1362019
Disentangling factors of variation using few labels
F Locatello, M Tschannen, S Bauer, G Rätsch, B Schölkopf, O Bachem
ICLR 2020 - 8th International Conference on Learning Representations, 2020
1202020
SOM-VAE: Interpretable discrete representation learning on time series
V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch
ICLR 2019 - Seventh International Conference on Learning Representations, 2018
1192018
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
J von Kügelgen, Y Sharma, L Gresele, W Brendel, B Schölkopf, ...
NeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, 2021
842021
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
MW Gondal, M Wüthrich, Đ Miladinović, F Locatello, M Breidt, V Volchkov, ...
NeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, 2019
822019
A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe
F Locatello, R Khanna, M Tschannen, M Jaggi
AISTATS 2017 - Proceedings of the 20th International Conference on Artifcial …, 2017
552017
On Disentangled Representations Learned From Correlated Data
F Träuble, E Creager, N Kilbertus, F Locatello, A Dittadi, A Goyal, ...
ICML 2021 - Proceedings of the 38th International Conference on Machine Learning, 2021
532021
On the transfer of disentangled representations in realistic settings
A Dittadi, F Träuble, F Locatello, M Wüthrich, V Agrawal, O Winther, ...
ICLR 2021 - 9th International Conference on Learning Representations, 2020
482020
The incomplete rosetta stone problem: Identifiability results for multi-view nonlinear ica
L Gresele, PK Rubenstein, A Mehrjou, F Locatello, B Schölkopf
UAI 2019 - Conference on Uncertainty in Artificial Intelligence, 2019
462019
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation
F Locatello, S Bauer, M Lucic, G Rätsch, S Gelly, B Schölkopf, O Bachem
Journal of Machine Learning Research (JMLR), 2020
342020
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
A Yurtsever, O Fercoq, F Locatello, V Cevher
ICML 2018 - Proceedings of the 35th International Conference on Machine Learning, 2018
342018
Boosting Variational Inference: an Optimization Perspective
F Locatello, R Khanna, J Ghosh, G Rätsch
AISTATS 2018 - Proceedings of the 21th International Conference on Artifcial …, 2017
322017
Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
F Locatello, M Tschannen, G Rätsch, M Jaggi
NIPS 2017 - Advances in Neural Information Processing Systems, 2017
262017
SCIM: universal single-cell matching with unpaired feature sets
SG Stark, J Ficek, F Locatello, X Bonilla, S Chevrier, F Singer, G Rätsch, ...
Bioinformatics 36 (Supplement_2), i919-i927, 2020
252020
Boosting Black Box Variational Inference
F Locatello, G Dresdner, R Khanna, I Valera, G Rätsch
NeurIPS 2018 - Advances in Neural Information Processing Systems (Spotlight), 2018
252018
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