Francesco Locatello

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHEmail yang diverifikasi di tuebingen.mpg.de
Stefan BauerHelmholtz | TUM | CIFAREmail yang diverifikasi di tum.de
Gunnar RätschProfessor, ETH ZürichEmail yang diverifikasi di inf.ethz.ch
Olivier BachemResearch Scientist, Google BrainEmail yang diverifikasi di google.com
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFAREmail yang diverifikasi di umontreal.ca
Frederik TräubleMax Planck Institute for Intelligent SystemsEmail yang diverifikasi di tuebingen.mpg.de
Sylvain GellyGoogle Brain ZurichEmail yang diverifikasi di m4x.org
Peter GehlerZalandoEmail yang diverifikasi di zalando.de
Andrea DittadiHelmholtz AI Munich | TUMEmail yang diverifikasi di tum.de
Julius von KügelgenETH ZürichEmail yang diverifikasi di stat.math.ethz.ch
Chris RussellAssociate Professor, University of OxfordEmail yang diverifikasi di oii.ox.ac.uk
Mario LučićResearch Scientist, Google DeepMindEmail yang diverifikasi di google.com
Dominik ZietlowLead Analyst, Second FoundationEmail yang diverifikasi di second-foundation.eu
Manuel WüthrichHarvard UniversityEmail yang diverifikasi di seas.harvard.edu
Max HornApplied Scientist in Causal Representation Learning, Amazon AWS AIEmail yang diverifikasi di amazon.de
Thomas BroxUniversity of FreiburgEmail yang diverifikasi di cs.uni-freiburg.de
Marco FumeroPostDoctoral Researcher, Institute of Science and Technology Austria (ISTA)Email yang diverifikasi di ist.ac.at
Michael TschannenGoogle DeepMindEmail yang diverifikasi di google.com
Emanuele RodolàProfessor of Computer Science, Sapienza University of RomeEmail yang diverifikasi di di.uniroma1.it
Georg HeigoldResearch Scientist, Google Inc.Email yang diverifikasi di google.com

Ikuti

Francesco Locatello

Assistant Professor, ISTA

Email yang diverifikasi di ista.ac.at - Beranda

Causality Deep Learning Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	1674	2019
Towards Causal Representation Learning B Schölkopf, F Locatello, S Bauer, NR Ke, N Kalchbrenner, A Goyal, ... Proceedings of the IEEE, 2021	1401	2021
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	878	2020
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	361	2020
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	321	2021
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	252	2019
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	224	2019
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	208	2020
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	200	2018
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	150	2019
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	140	2021
Bridging the gap to real-world object-centric learning M Seitzer, M Horn, A Zadaianchuk, D Zietlow, T Xiao, CJ Simon-Gabriel, ... ICLR 2023, 2023	131	2023
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	93	2019
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	91	2020
Relative representations enable zero-shot latent space communication L Moschella, V Maiorca, M Fumero, A Norelli, F Locatello, E Rodolà ICLR 2023 (Oral), 2023	89	2023
Score matching enables causal discovery of nonlinear additive noise models P Rolland, V Cevher, M Kleindessner, C Russel, B Schölkopf, D Janzing, ... ICML 2022, 2022	88	2022
Assaying out-of-distribution generalization in transfer learning F Wenzel, A Dittadi, PV Gehler, CJ Simon-Gabriel, M Horn, D Zietlow, ... NeurIPS 2022, 2022	78	2022
Visual representation learning does not generalize strongly within the same domain L Schott, J von Kügelgen, F Träuble, P Gehler, C Russell, M Bethge, ... ICLR 2022, 2022	75	2022
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	74	2020
Generalization and robustness implications in object-centric learning A Dittadi, S Papa, M De Vita, B Schölkopf, O Winther, F Locatello ICML 2022, 2022	72	2022

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