Francesco Locatello
Francesco Locatello
Senior Applied Scientist, Amazon AWS
Bestätigte E-Mail-Adresse bei amazon.com
Titel
Zitiert von
Zitiert von
Jahr
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
4912019
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
802019
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
712019
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
672020
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
642018
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
512020
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
502017
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
442020
Towards Causal Representation Learning
B Schölkopf*, F Locatello*, S Bauer, NR Ke, N Kalchbrenner, A Goyal, ...
Proceedings of the IEEE, 2021
422021
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
332019
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
242017
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
232017
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
212018
On Matching Pursuit and Coordinate Descent
F Locatello, A Raj, SP Reddy, G Rätsch, B Schölkopf, SU Stich, M Jaggi
ICML 2018 - Proceedings of the 35th International Conference on Machine Learning, 2018
212018
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
202019
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
202018
Competitive Training of Mixtures of Independent Deep Generative Models
F Locatello, D Vincent, I Tolstikhin, G Rätsch, S Gelly, B Schölkopf
arXiv preprint arXiv:1804.11130, 2018
20*2018
Stochastic Frank-Wolfe for Composite Convex Minimization
F Locatello, A Yurtsever, O Fercoq, V Cevher
NeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, 2019
132019
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, 2020
12*2020
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
102020
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