Francesco Locatello
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering
- Management Science and Operations Research top 10%
- Molecular Biology
- Co-authors
- Bernhard SchölkopfStefan BauerAnirudh GoyalYoshua BengioNal KalchbrennerNan Rosemary KeOlivier BachemGunnar Rätsch
- Topics
- Adversarial Robustness in Machine Learning (6 papers)Machine Learning and Data Classification (4 papers)Domain Adaptation and Few-Shot Learning (4 papers)
- Journals
- Proceedings of the IEEEJournal of Machine Learning Research2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Francesco Locatello
22 papers receiving 678 citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Artificial Intelligence 418
- Computer Vision and Pattern Recognition 168
- Control and Systems Engineering 47
- Management Science and Operations Research 42
- Molecular Biology 41
Countries citing papers authored by Francesco Locatello
This map shows the geographic impact of Francesco Locatello's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Francesco Locatello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Locatello more than expected).
Fields of papers citing papers by Francesco Locatello
This network shows the impact of papers produced by Francesco Locatello. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Francesco Locatello. The network helps show where Francesco Locatello may publish in the future.
Co-authorship network of co-authors of Francesco Locatello
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Locatello. A scholar is included among the top collaborators of Francesco Locatello based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Francesco Locatello. Francesco Locatello is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | On the Transfer of Disentangled Representations in Realistic Settings | 8 |
| 5 | Toward Causal Representation Learningbreakdown → | 519 |
| 6 | The Role of Pretrained Representations for the OOD Generalization of RL Agents | 2 |
| 7 | Backward-Compatible Prediction Updates: A Probabilistic Approach | 1 |
| 8 | Is Independence all you need? On the Generalization of Representations Learned from Correlated Data | 1 |
| 9 | Object-Centric Learning with Slot Attention | 13 |
| 10 | Disentangling Factors of Variations Using Few Labels | 21 |
| 11 | 2 | |
| 12 | Weakly-Supervised Disentanglement Without Compromises | 4 |
| 13 | 13 | |
| 14 | Are Disentangled Representations Helpful for Abstract Visual Reasoning | 31 |
| 15 | On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset | 14 |
| 16 | 6 | |
| 17 | Boosting Variational Inference: an Optimization Perspective | 2 |
| 18 | Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series | 6 |
| 19 | 1 | |
| 20 | 8 |
About Francesco Locatello
Francesco Locatello is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 27 papers that have together received 698 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Machine Learning and Data Classification (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Health Informatics (18 citations), Artificial Intelligence (418 citations) and Computer Vision and Pattern Recognition (168 citations). Francesco Locatello has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Bernhard Schölkopf, Stefan Bauer, Anirudh Goyal, Yoshua Bengio, Nal Kalchbrenner, Nan Rosemary Ke, Olivier Bachem, Gunnar Rätsch, Jürgen Schmidhuber and Sjoerd van Steenkiste. Their work appears in journals such as Proceedings of the IEEE, Journal of Machine Learning Research and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.