Dr. P.S.M. (Pascal) Mettes
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute
Bezoekadres
- Science Park 904
- Kamernummer: C3249
Postadres
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Postbus 94323
1090 GH Amsterdam
Contactgegevens
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Publicaties
- refereed (57)
- wetenschappelijk (1)
- erkenning (1)
- supervised theses (4)
- proefschrift (1)
- datasets (2)
2024
Bretti, C., Mettes, P., Koops, H. V., Odijk, D., & van Noord, N. (2024). Find the Cliffhanger: Multi-modal Trailerness in Soap Operas. In S. Rudinac, A. Hanjalic, C. Liem, M. Worring, B. Þ. Jónsson, B. Liu, & Y. Yamakata (Eds.), MultiMedia Modeling: 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29–February 2, 2024 : proceedings (Vol. II, pp. 199–212). (Lecture Notes in Computer Science; Vol. 14555). Springer. https://doi.org/10.1007/978-3-031-53308-2_15 [details]- Doorenbos, L., Márquez-Neila, P., Sznitman, R., & Mettes, P. (2024). Hyperbolic Random Forests. Transactions on Machine Learning Research, 2024, Article 2195. https://openreview.net/forum?id=pjKcIzvXWR [details]
- D’Amely di Melendugno, G. M., Flaborea, A., Mettes, P., & Galasso, F. (2024). Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation. In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems: IROS'24, Abu Dhabi, 14-18 October 2024 (pp. 13023–13030). IEEE. https://doi.org/10.1109/iros58592.2024.10801513 [details]
- Hu, V. T., Wu, D., Asano, Y. M., Mettes, P., Fernández-Méndez, F., Ommer, B., & Snoek, C. G. M. (2024). Flow Matching for Conditional Text Generation in a Few Sampling Steps. In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (Vol. 2, pp. 380-392). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.33 [details]
- Hu, V. T., Zhang, W., Tang, M., Mettes, P., Zhao, D., & Snoek, C. (2024). Latent Space Editing in Transformer-Based Flow Matching. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Proceedings of the 38th AAAI Conference on Artificial Intelligence: AAAI-2024 (Vol. 3, pp. 2247-2255). AAAI Press. https://doi.org/10.1609/aaai.v38i3.27998 [details]
- Ibrahimi, S., Ghadimi Atigh, M., van Noord, N., Mettes, P., & Worring, M. (2024). Intriguing Properties of Hyperbolic Embeddings in Vision-Language Models. Transactions on Machine Learning Research, 2024, Article 2113. https://openreview.net/forum?id=P5D2gfi4Gg [details]
- Mettes, P., Ghadimi Atigh, M., Keller-Ressel, M., Gu, J., & Yeung, S. (2024). Hyperbolic Deep Learning in Computer Vision: A Survey. International Journal of Computer Vision, 132(9), 3484-3508. https://doi.org/10.1007/s11263-024-02043-5 [details]
- Shi, Z., Mettes, P., & Snoek, C. G. M. (2024). Focus for Free in Density-Based Counting. International Journal of Computer Vision, 132(7), 2600-2617. https://doi.org/10.1007/s11263-024-01990-3 [details]
- Valenzuela, R. E. G., Mettes, P., Loos, B., Marquering, H., & Berkhout, E. (2024). Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset. BMC Oral Health, 24, Article 1325. https://doi.org/10.1186/s12903-024-05076-x [details]
2023
- Ayoughi, M., Mettes, P., & Groth, P. (2023). Self-Contained Entity Discovery from Captioned Videos. ACM Transactions on Multimedia Computing Communications and Applications, 19(5s), Article 177. https://doi.org/10.1145/3583138 [details]
- Burghouts, G., Cucchiara, R., Kasarla, T., Mettes, P., Van Der Pol, E., & Van Spengler, M. (2023). Maximum Class Separation as Inductive Bias in One Matrix. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 26, pp. 19553-19566). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2206.08704 [details]
- Chen, S., Du, Y., Mettes, P., & Snoek, C. G. M. (2023). Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph Generation. In ICMR'23: proceedings of the 2023 ACM International Conference on Multimedia Retrieval : Thessaloniki, Greece, June 12-15, 2023 (pp. 39-47). Association for Computing Machinery. https://doi.org/10.48550/arXiv.2306.10122, https://doi.org/10.1145/3591106.3592267 [details]
- Mensink, T., & Mettes, P. (2023). Infinite Class Mixup. In The 34th British Machine Vision Conference Proceedings: BMVC 2023 : 20th-24th November 2023, Aberdeen, UK Article 135 BMVA Press. https://doi.org/10.48550/arXiv.2305.10293 [details]
- Mettes, P. (2023). Hyperbolic Graph Codebooks. In G. Nicosia, V. Ojha, E. La Malfa, G. La Malfa, P. Pardalos, G. Di Fatta, G. Giuffrida, & R. Umeton (Eds.), Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers (Vol. I, pp. 48-61). (Lecture Notes in Computer Science; Vol. 13810). Springer. https://doi.org/10.1007/978-3-031-25599-1_5 [details]
- Mettes, P. (2023). Universal Prototype Transport for Zero-Shot Action Recognition and Localization. International Journal of Computer Vision, 131(11), 3060-3073. https://doi.org/10.1007/s11263-023-01846-2 [details]
- van Spengler, M., Berkhout, E., & Mettes, P. (2023). Poincaré ResNet. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 5396-5405). IEEE Computer Society. https://doi.org/10.48550/arXiv.2303.14027, https://doi.org/10.1109/ICCV51070.2023.00499 [details]
- van Spengler, M., Wirth, P., & Mettes, P. (2023). HypLL: The Hyperbolic Learning Library. In MM '23: Proceedings of the 31st ACM International Conference on Multimedia : Oct 29-Nov 3m 2023, Ottawa, Canada (pp. 9676–9679). Association for Computing Machinery. https://doi.org/10.1145/3581783.3613462 [details]
2022
- Byvshev, P., Mettes, P., & Xiao, Y. (2022). Are 3D convolutional networks inherently biased towards appearance? Computer Vision and Image Understanding, 220, Article 103437. https://doi.org/10.1016/j.cviu.2022.103437 [details]
- Ghadimi Atigh, M., Keller-Ressel, M., & Mettes, P. (2022). Hyperbolic Busemann Learning with Ideal Prototypes. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6-14 December 2021 (Vol. 1, pp. 103-115). (Advances in Neural Information Processing Systems; Vol. 34). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2021/hash/01259a0cb2431834302abe2df60a1327-Abstract.html [details]
- GhadimiAtigh, M., Schoep, J., Acar, E., van Noord, N., & Mettes, P. (2022). Hyperbolic Image Segmentation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 4443-4452). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR52688.2022.00441 [details]
- Schutte, J., & Mettes, P. (2022). Teaching a New Dog Old Tricks: Contrastive Random Walks in Videos with Unsupervised Priors. In ICMR '22: proceedings of the 2022 International Conference on Multimedia Retrieval : June 27-30, 2022, Newark, NJ, USA (pp. 176-184). The Association for Computing Machinery. https://doi.org/10.1145/3512527.3531376 [details]
- Shi, Z., Mettes, P., Maji, S., & Snoek, C. G. M. (2022). On Measuring and Controlling the Spectral Bias of the Deep Image Prior. International Journal of Computer Vision, 130(4), 885–908. https://doi.org/10.1007/s11263-021-01572-7 [details]
- Yang, P., Asano, Y. M., Mettes, P., & Snoek, C. G. M. (2022). Less than Few: Self-Shot Video Instance Segmentation. In S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, & T. Hassner (Eds.), Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 : proceedings (Vol. XXXIV, pp. 449–466). (Lecture Notes in Computer Science; Vol. 13694). Springer. https://doi.org/10.1007/978-3-031-19830-4_26 [details]
- Ülger, O., Wiederer, J., Ghafoorian, M., Belagiannis, V., & Mettes, P. (2022). Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs. In The 33rd British Machine Vision Conference Proceedings: BMVC 2022 : 21st-24th November 2022, London, UK Article 968 BMVA Press. https://bmvc2022.mpi-inf.mpg.de/968/ [details]
2021
- Bretti, C., & Mettes, P. (2021). Zero-Shot Action Recognition from Diverse Object-Scene Compositions. In 32nd British Machine Vision Conference 2021: BMVC 2021, Online, November 22-25, 2021 Article 281 BMVA Press. [details]
- Chen, S., Mettes, P., & Snoek, C. G. M. (2021). Diagnosing Errors in Video Relation Detectors. In 32nd British Machine Vision Conference 2021: BMVC 2021, Online, November 22-25, 2021 Article 241 BMVA Press. [details]
- Chen, S., Shi, Z., Mettes, P., & Snoek, C. G. M. (2021). Social fabric: Tubelet compositions for video relation detection. In 2021 IEEE/CVF International Conference on Computer Vision: proceedings : ICCV 2021 : 11-17 October 2021, virtual event (pp. 13465-13474). (International Conference on Computer Vision; Vol. 18). IEEE Computer Society. https://doi.org/10.1109/ICCV48922.2021.01323 [details]
- Mettes, P., Thong, W., & Snoek, C. G. M. (2021). Object priors for classifying and localizing unseen actions. International Journal of Computer Vision, 129(6), 1954–1971. https://doi.org/10.1007/s11263-021-01454-y [details]
- Shi, Z., Chen, Y., Gavves, E., Mettes, P., & Snoek, C. G. M. (2021). Unsharp Mask Guided Filtering. IEEE Transactions on Image Processing, 30, 7472-7485. https://doi.org/10.1109/TIP.2021.3106812 [details]
- Yang, P., Mettes, P., & Snoek, C. G. M. (2021). Few-Shot Transformation of Common Actions into Time and Space. In Proceedings, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition: virtual, 9-25 June 2021 (pp. 16026-16035). (CVPR). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.48550/arXiv.2104.02439, https://doi.org/10.1109/CVPR46437.2021.01577 [details]
2020
- Byvshev, P., Mettes, P., & Xiao, Y. (2020). Heterogeneous Non-Local Fusion for Multimodal Activity Recognition. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 63-72). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390675 [details]
- Chen, S., Mettes, P., Hu, T., & Snoek, C. G. M. (2020). Interactivity Proposals for Surveillance Videos. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 108-116). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390680 [details]
- Chen, Y., Hu, V. T., Gavves, E., Mensink, T., Mettes, P., Yang, P., & Snoek, C. G. M. (2020). PointMixup: Augmentation for Point Clouds. In A. Vedaldi, H. Bischof, T. Brox, & J. M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. III, pp. 330-345). (Lecture Notes in Computer Science; Vol. 12348). Springer. https://doi.org/10.1007/978-3-030-58580-8_20 [details]
- Dijt, P., & Mettes, P. (2020). Trajectory Prediction Network for Future Anticipation of Ships. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 73-81). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390676 [details]
- Long, T., Mettes, P., Shen, H. T., & Snoek, C. (2020). Searching for Actions on the Hyperbole. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : virtual, 14-19 June 2020 (pp. 1138-1147). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR42600.2020.00122 [details]
- Mettes, P., Koelma, D. C., & Snoek, C. G. M. (2020). Shuffled ImageNet Banks for Video Event Detection and Search. ACM Transactions on Multimedia Computing Communications and Applications, 16(2), Article 44. https://doi.org/10.1145/3377875 [details]
- Mettes, P., Van Der Pol, E., & Snoek, C. (2020). Hyperspherical Prototype Networks. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019 (pp. 1476-1486). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/02a32ad2669e6fe298e607fe7cc0e1a0-Abstract.html [details]
- Thong, W., Mettes, P., & Snoek, C. G. M. (2020). Open Cross-Domain Visual Search. Computer Vision and Image Understanding, 200, Article 103045. https://doi.org/10.1016/j.cviu.2020.103045 [details]
- Yang, P., Hu, V. T., Mettes, P., & Snoek, C. G. M. (2020). Localizing the Common Action Among a Few Videos. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. VII, pp. 505-521). (Lecture Notes in Computer Science; Vol. 12352). Springer. https://doi.org/10.1007/978-3-030-58571-6_30 [details]
- Zuanazzi, V., van Vugt, J., Booij, O., & Mettes, P. (2020). Adversarial Self-Supervised Scene Flow Estimation. In 2020 International Conference on 3D Vision: 3DV 2020 : proceedings : 25-28 November 2020, virtual event (pp. 1049-1058). IEEE Computer Society. https://doi.org/10.1109/3DV50981.2020.00115 [details]
2019
- Brown, A., Mettes, P., & Worring, M. (2019). 4-Connected Shift Residual Networks. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 1990-1997). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00248 [details]
- Hommos, O., Pintea, S. L., Mettes, P. S. M., & van Gemert, J. C. (2019). Using phase instead of optical flow for action recognition. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops: Munich, Germany, September 8-14, 2018 : proceedings (Vol. VI, pp. 678-691). (Lecture Notes in Computer Science; Vol. 11134). Springer. https://doi.org/10.1007/978-3-030-11024-6_51 [details]
- Hu, T., Mettes, P., Huang, J.-H., & Snoek, C. G. M. (2019). SILCO: Show a Few Images, Localize the Common Object. In Proceedings, 2019 International Conference on Computer Vision: 27 October-2 November 2019, Seoul, Korea (pp. 5066-5075). (ICCV). IEEE Computer Society. https://doi.org/10.1109/ICCV.2019.00517 [details]
- Ibrahimi, S., Chen, S., Arya, D., Câmara, A., Chen, Y., Crijns, T., van der Goes, M., Mensink, T., van Miltenburg, E., Odijk, D., Thong, W., Zhao, J., & Mettes, P. (2019). Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching. In MM'19: proceedings of the 27th ACM Conference on Multimedia : October 21-25, 2019, Nice, France (pp. 2196-2198). Association for Computing Machinery. https://doi.org/10.1145/3343031.3350597 [details]
- Mettes, P., & Snoek, C. G. M. (2019). Pointly-Supervised Action Localization. International Journal of Computer Vision, 127(3), 263–281. https://doi.org/10.1007/s11263-018-1120-4 [details]
- Shi, Z., Mettes, P., & Snoek, C. G. M. (2019). Counting with Focus for Free. In Proceedings, 2019 International Conference on Computer Vision: 27 October-2 November 2019, Seoul, Korea (pp. 4199-4208). (ICCV). IEEE Computer Society. https://doi.org/10.1109/ICCV.2019.00430 [details]
- de la Riva, M., & Mettes, P. (2019). Bayesian 3D ConvNets for Action Recognition from Few Examples. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 1337-1343). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00169 [details]
2017
- Mensink, T., Jongstra, T., Mettes, P., & Snoek, C. G. M. (2017). Music-Guided Video Summarization using Quadratic Assignments. In ICMR '17: proceedings of the 2017 ACM International Conference on Multimedia Retrieval : June 6-9, 2017, Bucharest, Romania (pp. 58-64). The Association for Computing Machinery. https://doi.org/10.1145/3078971.3079024 [details]
- Mettes, P., & Snoek, C. G. M. (2017). Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions. In 2017 IEEE International Conference on Computer Vision : ICCV 2017: proceedings : 22-29 October 2017, Venice, Italy (pp. 4453-4462). IEEE Computer Society. https://doi.org/10.1109/ICCV.2017.476 [details]
- Mettes, P., Snoek, C. G. M., & Chang, S.-F. (2017). Localizing Actions from Video Labels and Pseudo-Annotations. In T. K. Kim, S. Zafeiriou, G. Brostow, & K. Mikolajczyk (Eds.), Proceedings of the British Machine Vision Conference 2017 Article 22 BMVA Press. https://doi.org/10.5244/C.31.22 [details]
2016
- Mettes, P., Koelma, D. C., & Snoek, C. G. M. (2016). The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection. In ICMR'16: proceedings of the 2016 ACM International Conference on Multimedia Retrieval: June 6-9, 2016, New York, NY, USA (pp. 175-182). Association for Computing Machinery. https://doi.org/10.1145/2911996.2912036 [details]
- Mettes, P., van Gemert, J. C., & Snoek, C. G. M. (2016). No Spare Parts: Sharing Part Detectors for Image Categorization. Computer Vision and Image Understanding, 152, 131-141. https://doi.org/10.1016/j.cviu.2016.07.008 [details]
- Mettes, P., van Gemert, J. C., & Snoek, C. G. M. (2016). Spot On: Action Localization from Pointly-Supervised Proposals. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016 : proceedings (Vol. 5, pp. 437-453). (Lecture Notes in Computer Science; Vol. 9909). Springer. https://doi.org/10.1007/978-3-319-46454-1_27 [details]
2015
- Mettes, P., van Gemert, J. C., Cappallo, S., Mensink, T., & Snoek, C. G. M. (2015). Bag-of-Fragments: Selecting and encoding video fragments for event detection and recounting. In ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China (pp. 427-434). Association for Computing Machinery. https://doi.org/10.1145/2671188.2749404 [details]
- Snoek, C. G. M., Cappallo, S., Fontijne, D., Julian, D., Koelma, D. C., Mettes, P., van de Sande, K. E. A., Sarah, A., Stokman, H., & Towal, R. B. (2015). Qualcomm Research and University of Amsterdam at TRECVID 2015: Recognizing Concepts, Objects, and Events in Video. In 2015 TREC Video Retrieval Evaluation: notebook papers and slides National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv15.papers/mediamill.pdf [details]
- van Gemert, J. C., Verschoor, C. R., Mettes, P., Epema, K., Koh, L. P., & Wich, S. (2015). Nature Conservation Drones for Automatic Localization and Counting of Animals. In L. Agapito, M. M. Bronstein, & C. Rother (Eds.), Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014: proceedings (Vol. 1, pp. 255-270). (Lecture Notes in Computer Science ; Vol. 8925). Springer. https://doi.org/10.1007/978-3-319-16178-5_17 [details]
2014
- Snoek, C. G. M., van de Sande, K. E. A., Fontijne, D., Cappallo, S., van Gemert, J., Habibian, A., Mensink, T., Mettes, P., Tao, R., Koelma, D. C., & Smeulders, A. W. M. (2014). MediaMill at TRECVID 2014: Searching Concepts, Objects, Instances and Events in Video. In 2014 TREC Video Retrieval Evaluation: notebook papers and slides National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv14.papers/mediamill.pdf [details]
2023
- Hu, T., Thong, W., Mettes, P., & Snoek, C. G. M. (2023). Query by Activity Video in the Wild. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2311.13895 [details]
Prijs / subsidie
- Snoek, C., Mettes, P., Janssen, H., Blanke, T., Groen, I. & Rudinac, S. (2023). Artificial Intelligence for video from a multidisciplinary perspective. https://dsc.uva.nl/programmes/interdisciplinary-phd-programme/hava-lab/hava-lab.html
2023
2025
- Gonzalez Valenzuela, R., Berkhout, E., Marquering, H., Mettes, P. & Loos, B. (2025). ACTA-DIRECT Dataset v2. Vrije Universiteit Amsterdam. https://doi.org/10.48338/vu01-h5alyj
2024
- Gonzalez Valenzuela, R., Berkhout, E., Marquering, H., Mettes, P. & Loos, B. (2024). ACTA-DIRECT Dataset. Vrije Universiteit Amsterdam. https://doi.org/10.48338/vu01-wk8sqn
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Nevenwerkzaamheden
- Geen nevenwerkzaamheden
Bretti, C., Mettes, P., Koops, H. V., Odijk, D., & van Noord, N. (2024). Find the Cliffhanger: Multi-modal Trailerness in Soap Operas. In S. Rudinac, A. Hanjalic, C. Liem, M. Worring, B. Þ. Jónsson, B. Liu, & Y. Yamakata (Eds.), MultiMedia Modeling: 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29–February 2, 2024 : proceedings (Vol. II, pp. 199–212). (Lecture Notes in Computer Science; Vol. 14555). Springer.