Publications by ELLIS Alicante

2024

Gulati, A., Martinez-Garcia, M., Lepri, B., & Oliver, N. (2024). What is beautiful is still good, especially if you are man: The Attractiveness Halo Effect in the era of AI-based Beauty Filters. International Conference on Computational Social Science.
Riccio, P., Hofmann, T., & Oliver, N. (2024). Exposed or Erased: Algorithmic Censorship of Nudity in Art. CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems, 1-17.
Riccio, P., Colin, J., Ogolla, S., & Oliver, N. (2024). Mirror, Mirror on the wall, who is the whitest of all? Racial biases in social media beauty filters. Social Media and Society, 10(2), 20563051241239295.
Riccio, P., & Oliver, N. (2024). A Techno-Feminist Perspective on the Algorithmic Censorship of Artistic Nudity. Bibliotheca Hertziana–Max Planck Institute for Art History, 3.
Arnaiz-Rodríguez, A., Curto, G., & Oliver, N. (2024). Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance. WWW 2024 Workshop on Trustworthy Learnin on Graphs (TrustLOG).
Arnaiz-Rodríguez, A., & Oliver, N. (2024). Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values. ICLR 2024 Workshop on Data-centric Machine Learning Research (DMLR).
Bolt, K., Gil-González, D., & Oliver, N. (2024). Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic. Frontiers of Public health, 12, 1350743.
Favero, L. A., Pérez-Ortiz, J. A., Käser, T., & Oliver, N. (2024). Towards Student-Centric AI-Supported Learning: Teaching Chatbots to Ask the Right Questions. Collaborative AI and Modeling of Humans, AAAI Bridge Program.
Derner, E., Kučera, D., Oliver, N., & Zahálka, J. (2024). Can ChatGPT Read Who You Are?. Collaborative AI and Modeling of Humans, AAAI Bridge Program.

2023

Derner, E., Kučera, D., Oliver, N., & Zahálka, J. (2023). Can ChatGPT Read Who You Are?. arXiv:2312.16070.
Fel, T., Boissin, T., Boutin, V., Picard, A., Novello, P., Colin, J., Linsley, D., Rousseau, T., Cadène, R., Gardes, L., & Serre, T. (2023). Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. 37th Conference on Neural Information Processing Systems (NeurIPS), 36, 37813-37826.
Begga, A., Garibo I Orts, O., De Maria Garcia, S., Escolano, F., Lozano, M.A., Oliver, N., & Conejero, J.A. (2023). Predicting COVID19 pandemic waves including vaccination data with deep learning. Frontiers of Public health, 11, 1279364.
Németh, G. D., Lozano, M. A., Quadrianto, N., & Oliver, N. (2023). Addressing Membership Inference Attack in Federated Learning with Model Compression. arXiv preprint:2311.17750.
Derner, E., Batistič, K., Zahálka, J., & Babuška, R. (2023). A Security Risk Taxonomy for Large Language Models. arXiv preprint arXiv:2311.11415.
Boutin, V., Fel, T., Singhal, L., Mukherji, R., Nagaraj, A., Colin, J., & Serre, T. (2023). Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?. Proceedings of the International Conference on Machine Learning (ICML), 2953-3002.
Fel, T., Picard, A., Bethune, L., Boissin, T., Vigouroux, D., Colin, J., Cadène, R., & Serre, T. (2023). CRAFT: Concept Recursive Activation FacTorization for Explainability. Conference on Computer Vision and Pattern Recognition (CVPR), 2711-2721.
Curto, G., Arnaiz-Rodríguez, A., & Oliver, N. (2023). Algorithms for Social Justice: Affirmative Action in Social Networks. arXiv:2305.03223.
Arnaiz-Rodríguez, A., Escolano, F., & Oliver, N. (2023). FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values. arXiv:2303.01928.
Letouzé, E., Oliver, N., Lepri, B., & Vinck, P. (2023). AI FOR THE SDGS—AND BEYOND? TOWARDS A HUMAN AI CULTURE FOR DEVELOPMENT AND DEMOCRACY. Missing Links in AI Governance by UNESCO and MILA, 162-189.
Oliver, N. (2023). A Philosopher's Daughter Navigates a Career in AI. Communications of the ACM, 13-13.
Riccio, P., & Oliver, N. (2023). Racial Bias in the Beautyverse: Evaluation of Augmented-Reality Beauty Filters. European Conference on Computer Vision 2022, 13803, 714-721.

2022

Németh, G. D., Lozano, M. A., Quadrianto, N., & Oliver, N. (2022). A Snapshot of the Frontiers of Client Selection in Federated Learning. Transactions on Machine Learning Research.
Arnaiz-Rodríguez, A., Begga, A., Escolano, F., & Oliver, N. (2022). DiffWire: Inductive Graph Rewiring via the Lovász Bound. Proceedings of the First Learning on Graphs Conference, PMLR, 198, 15:1-15:27.
Zerroug, A., Vaishnav, M., Colin, J., Musslick, S., & Serre, T. (2022). A Benchmark for Compositional Visual Reasoning. 36th Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks, 35, 29776-29788.
Colin, J., Fel, T., Cadène, R., & Serre, T. (2022). What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. 36th Conference on Neural Information Processing Systems (NeurIPS).
Fuente, D., Hervás, D., Rebollo, M., Conejero, J.A., & Oliver, N. (2022). COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave. Frontiers of Public Health, 10.
Gulati, A., Lozano, M. A., Lepri, B., & Oliver, N. (2022). BIASeD: Bringing Irrationality into Automated System Design. Thinking Fast and Slow and Other Cognitive Theories in AI, AAAI Fall Symposium 2022.
Martínez-García, M., Sansano-Sansano, E., Castillo-Hornero, A., Femenia, R., Roomp, K., & Oliver, N. (2022). Social Isolation during the COVID-19 Pandemic in Spain: A Population Study. Nature Scientific Reports, 12(1), 1-15.
Top 8% of research outputs scored by Altmetric
Lozano, M.A., Garibo, O., Piñol, E., Rebollo, M., Polotskaya, K., Garcia-March, M. A., Conejero, J. A., Escolano, F., & Oliver, N. (2022). Open Data Science to fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge. International Joint Conference on Artificial Intelligence Organization (IJCAI), 5304-5308.
Best paper award track from sister conferences
Riccio, P., Psomas, B., Galati, F., Escolano, F., Hofmann, T., & Oliver, N. (2022). OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters. 36th Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track.
Conejero, A. J., & Oliver, N. (2022). La iniciativa Valencia IA4COVID. Indice: Revista de Estadística y Sociedad, 1(86), 33-35.
Oliver, N. (2022). SRIP Report 2022. SRIP Report of the European Commission, 664-707.
Riccio, P., Oliver, J. L., Escolano, F., & Oliver, N. (2022). Algorithmic Censorship of Art: A Proposed Research Agenda. 13th International Conference on Computational Creativity.
Fel, T., Hervier, L., Vigouroux, D., Poche, A., Plakoo, J., Cadène, R., Chalvidal, M., Colin, J., Boissin, T., Bethune, L., Picard, A., Nicodeme, C., Gardes, L., Flandin, G., & Serre, T. (2022). Xplique: A Deep Learning Explainability Toolbox. Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Explainable Artificial Intelligence for Computer Vision (XAI4CV).
Cauchard, J., Jarke, M., & Oliver, N. (2022). Communications of the ACM Europe Special Section. Communications of the ACM, 65(4), 32-34.
Riccio, P., Galati, F., Zuluaga, M. A., De Martin, J. C., & Nichele, S. (2022). Translating Emotions from EEG to Visual Arts. International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar), 243-258.
Alt, F., Kostakos, V., & Oliver, N. (2022). Out-of-the-Lab Pervasive Computing. IEEE Pervasive Computing Journal, 21(1), 7-8.
Olivares Gil, A., Arnaiz Rodríguez, A., Ramírez Sanz, J. M., Garrido Labrador, J. L., Ahedo García, V., García Osorio, C., Santos Martín, J. I., & Galán Ordax, J. M. (2022). Mapping the scientific structure of organization and management of enterprises using complex networks. International Journal of Production Management and Engineering, 10(1), 65-76.
De Nadai, M., Roomp, K., Lepri, B., & Oliver, N. (2022). The Impact of Control and Mitigation Strategies during the Second Wave of coronavirus Infections in Spain and Italy. Nature Scientific Reports, 12(1), 1-13.

2021

Xue, H., Salim, F. D., Ren, Y., & Oliver, N. (2021). MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction. Advances in Neural Information Processing Systems, 34, 30380-30391.
Martinez-Garcia, M., Rabasa, A., Barber, X., Polotskaya, K., Roomp, K., & Oliver, N. (2021). Key factors affecting people’s unwillingness to be confined during the COVID-19 pandemic in Spain: a large-scale population study. Nature Scientific Reports, 11, 1-18.
In the top 6% of all research outputs scored by Altmetric
Lozano, M.A., Garibo, O., Piñol, E., Rebollo, M., Polotskaya, K., Garcia-March, M. A., Conejero, J. A., Escolano, F., & Oliver, N. (2021). Open Data Science to fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge. Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 384-399.
Best paper award!
Riccio, P., Bergaust, K., Christensen-Scheel, B., De Martin, J. C., Zuluaga, M. A., & Nichele, S. (2021). AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aesthetics. Politics of the Machines.
Luca, M., Barlacchi, G., Oliver, N., & Lepri, B. (2021). Leveraging Mobile Phone Data for Migration Flows. arXiv preprint arXiv:2105.14956.
Lepri, B., Oliver, N., & Pentland, A. (2021). Ethical machines: The human-centric use of artificial intelligence. iScience, 24(3), 102249.
Nanni, M., Andrienko, G., Barabási, A. L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertesz, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. M., Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., Van Den Hoven, J., & Vespignani, A. (2021). Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. iScience, 23(1), 1-6.
In the top 4% of all research outputs scored by Altmetric

2020

Oliver, N., Barber, X., Roomp, K., & Roomp, K. (2020). Assessing the Impact of the COVID-19 Pandemic in Spain: Large-Scale, Online, Self-Reported Population Survey. Journal of Medical Internet Research, 22(9), e21319.
In the top 5% of all research outputs scored by Altmetric
Oliver, N., Lepri, B., Sterly, H., Lambiotte, R., Deletaille, S., De Nadai, M., Letouzé, E., Salah, A. A., Benjamins, R., Cattuto, C., Colizza, V., de Cordes, N., Fraiberger, S. P., Koebe, T., Lehmann, S., Murillo, J., Pentland, A., Pham, P. N, Pivetta, F., Saramäki, J., Scarpino, S. V., Tizzoni, M., Verhulstand, S., & Vinck, P. (2020). Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Science Advances, 6(23), eabc0764.
In the top 5% of all research outputs scored by Altmetric
Roomp, K., & Oliver, N. (2020). ACDC-Tracing: Towards Anonymous Citizen-Driven Contact Tracing. arXiv preprint arXiv:2004.07463.
Oliver, N., Letouzé, E., Sterly, H., Delataille, S., De Nadai, M., Lepri, B., Lambiotte, R., Benjamins, R., Cattuto, C., Colizza, V., de Cordes, N., Fraiberger, S. P., Koebe, T., Lehmann, S., Murillo, J., Pentland, A., Pham, P. N., Pivetta, F., Salah, A. A., Saramäki, J., Scarpino, S. V., Tizzoni, M., Verhulst, S., & Vinck, P. (2020). Mobile phone data and COVID-19: Missing an opportunity?. arXiv preprint arXiv:2003.12347.