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Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 16 Peace, Justice and Strong Institutions
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Dive into the research topics where Éric Granger is active. These topics are generated from this person's research output (titles and abstracts), as well as their research interests, awards, and organizations associated with them. Together, they form a unique digital fingerprint.
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Collaborations and top research areas from the last five years
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Research output
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Beyond Patches: Mining Interpretable Part-Prototypes for Explainable AI
Alehdaghi, M., Bhattacharya, R., Shamsolmoali, P., Cruz, R. M. O., Heritier, M. & Granger, E., 2026, Proceedings of the AAAI Conference on Artificial Intelligence. Koenig, S., Jenkins, C. & Taylor, M. E. (eds.). 44 ed. Association for the Advancement of Artificial Intelligence, p. 37213-37221 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 40, no. 44).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review
Open Access -
DogFit: Domain-guided Fine-tuning for Efficient Transfer Learning of Diffusion Models
Bahram, Y., Shateri, M. & Granger, E., 2026, Proceedings of the AAAI Conference on Artificial Intelligence. Koenig, S., Jenkins, C. & Taylor, M. E. (eds.). 4 ed. Association for the Advancement of Artificial Intelligence, p. 2345-2353 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 40, no. 4).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review
Open Access -
Learning from Stochastic Teacher Representations Using Student-Guided Knowledge Distillation
Aslam, M. H., Martinez, C., Pedersoli, M., Koerich, A. L., Etemad, A. & Granger, E., 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P., Jorge, A. M. & Abreu, P. H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 235-253 19 p. (Lecture Notes in Computer Science; vol. 16018 LNCS).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review
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MTLoc: A Confidence-Based Source-Free Domain Adaptation Approach for Indoor Localization
Mehregan, N., Bozkurt, B., Granger, E., Hajikhani, M. & Shateri, M., 2026, In: IEEE Sensors Journal. 26, 2, p. 2524-2534 11 p.Research output: Contribution to journal › Journal Article › peer-review
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Progressive Multi-Source Domain Adaptation for Personalized Facial Expression Recognition
Zeeshan, M. O., Pedersoli, M., Koerich, A. L. & Granger, E., 2026, In: IEEE Transactions on Affective Computing. 17, 1, p. 575-586 12 p.Research output: Contribution to journal › Journal Article › peer-review