Stephan, A, Miklautz, L, Leiber, C, Araujo, PHLD, Repas, D, Plant, C & Roth, B 2024, Text-Guided Alternative Image Clustering. in C Zhao, M Mosbach, P Atanasova, S Goldfarb-Tarrent, P Hase, A Hosseini, M Elbayad, S Pezzelle & M Mozes (eds), Proceedings of the 9th Workshop on Representation Learning for NLP (RepL4NLP-2024). ACL Anthology, Kerrville, pp. 177-190. <https://aclanthology.org/2024.repl4nlp-1.13/>

Stephan, A, Miklautz, L, Sidak, K, Wahle, JP, Gipp, B, Plant, C & Roth, B 2024, Text-Guided Image Clustering. in Y Graham & M Purver (eds), 18th Conference of the European Chapter of the Association for Computational Linguistics : Proceedings of the Conference, Vol. 1 (Long Papers). ACL Anthology, Kerrville, pp. 2960-2976, 18th Conference of the European Chapter of the Association for Computational Linguistics, Malta, 17/03/24. https://doi.org/10.18653/v1/2024.eacl-long.180

Kritzinger, S , Pfaff, K, Barta, JMT, Bernhard, J, Eder, A, Forgó, N, Paspalj, F, Plant, C , Prainsack, B, Prandner, D, Rittel, S & Tschiatschek, S 2023, 'Digitize! – Computational Social Science in der digitalen und sozialen Transformation', Zeitschrift für Hochschulentwicklung, pp. 173 - 195. https://doi.org/10.21240/zfhe/SH-F/11

Leiber, C, Miklautz, L, Plant, C & Böhm, C 2023, Application of Deep Clustering Algorithms. in CIKM 2023 - Proceedings of the 32nd ACM International Conference on Information and Knowledge Management: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. ACM, pp. 5208-5211. https://doi.org/10.1145/3583780.3615290

Velaj, Y , Dolezal, D , Ambros, R , Plant, C & Motschnig, R 2023, Teaching Data Science to Non-Computer Science Students: A Learner-Centered Approach. in 2023 IEEE Frontiers in Education Conference (FIE). pp. 1-9, 2023 IEEE Frontiers in Education Conference (FIE), College Station, Texas, Texas, United States, 18/10/23. https://doi.org/10.1109/FIE58773.2023.10343463

Chen, Z, Wu, Z, Zhong, L, Plant, C, Wang, S & Guo, W 2023 'Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphs' arXiv. https://doi.org/10.48550/arXiv.2304.06336

Bauer, LGM, Leiber, C, Böhm, C & Plant, C 2023, Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering. in Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023. SIAM, pp. 109-117. <http://eprints.cs.univie.ac.at/7934/>

Sun, X, Song, Z, Yu, Y, Dong, J, Plant, C & Böhm, C 2023, 'Network Embedding via Deep Prediction Model', IEEE Transactions on Big Data, vol. 9, no. 2, pp. 455-470. https://doi.org/10.1109/TBDATA.2022.3194643

Foerster, K-T, Marette, T, Neumann, S, Plant, C , Sadikaj, Y, Schmid, S & Velaj, Y 2023, Analyzing the Communication Clusters in Datacenters. in Y Ding, J Tang, JF Sequeda, L Aroyo, C Castillo & G-J Houben (eds), Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023. ACM, New York, pp. 3022-3032. https://doi.org/10.1145/3543507.3583410

Sadikaj, Y, Rass, J, Velaj, Y & Plant, C 2023, Semi-Supervised Embedding of Attributed Multiplex Networks. in Y Ding, J Tang, JF Sequeda, L Aroyo, C Castillo & G-J Houben (eds), Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023. ACM, New York, pp. 578-587. https://doi.org/10.1145/3543507.3583485

Ambros, R, Bernsteiner, A, Bloem, R, Dolezal, D, Garzia, D, Göltl, K, Haagen-Schützenhöfer, C, Hadler, M, Hell, T, Herderich, A, Jercic, P, Kayali, F, Kemény, F, Kirsch, C, Kloesch, B, Kocher, D, Landerl, K, Lasser, J, Lex, E, Motschnig, R , Plant, C, Posch, L, Reiter-Haas, M, Schubatzky, T, Slany, W, Sokolova, A, Spitzer, P, Steinböck, M, Velaj, Y & Yüksel-Arslan, P 2023, 'Two-Year Progress of Pilot Research Activities in Teaching Digital Thinking Project (TDT)', Zeitschrift für Hochschulentwicklung, vol. 18, no. Sonderheft Hochschullehre, pp. 117-136. https://doi.org/10.3217/zfhe-SH-HL/07

Chen, Z, Wu, Z, Lin, Z, Wang, S, Plant, C & Guo, W 2023 'AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing' arXiv. https://doi.org/10.48550/arXiv.2304.07014

Leiber, C, Miklautz, L, Plant, C & Böhm, C 2023, Benchmarking Deep Clustering Algorithms With ClustPy. in J Wang, Y He, TN Dinh, C Grant, M Qiu & W Pedrycz (eds), Proceedings - 23rd IEEE International Conference on Data Mining Workshops: ICDMW 2023. IEEE, pp. 625-632. https://doi.org/10.1109/ICDMW60847.2023.00087

Weber, P, Miklautz, L, Kumar, A, Grosse-Wentrup, M & Plant, C 2023, CaFe DBSCAN: A Density-based Clustering Algorithm for Causal Feature Learning. in The 10th IEEE International Conference on Data Science and Advanced Analytics.

Projects

Clustering of Smart-Meter Data

Velaj, Y. (Project Lead) & Plant, C. (Co-Lead)

1/01/24 → 31/12/26

Project: Research cooperation

Learning Synchronization Patterns in Neural Signal

Plant, C. (Project Lead) & Schindlerova, K. (Co-Lead)

1/10/21 → 30/09/24

Project: Research funding

Hybrid Computational Sciences

Grohs, P. (Project Lead), Scherzer, O. (Co-Lead), Plant, C. (Co-Lead), Dellago, C. (Co-Lead), Wöhrer, A. (Co-Lead), Kunisch, K. (Co-Lead), Ramlau, R. (Co-Lead) & von Haeseler, A. (Co-Lead)

16/08/21 → 31/12/21

Project: Research funding