| Project codenet: a large-scale AI for code dataset for learning a diversity of coding tasks R Puri, DS Kung, G Janssen, W Zhang, G Domeniconi, V Zolotov, J Dolby, ... Advances in Neural Information Processing Systems, 2021 | 305* | 2021 |
| Directed acyclic graph neural networks V Thost, J Chen International Conference on Learning Representations (ICLR), 2021 | 129 | 2021 |
| Exploring software naturalness through neural language models L Buratti, S Pujar, M Bornea, S McCarley, Y Zheng, G Rossiello, A Morari, ... arXiv preprint arXiv:2006.12641, 2020 | 114 | 2020 |
| Temporal Query Answering in the Description Logic DL-Lite S Borgwardt, M Lippmann, V Thost International Symposium on Frontiers of Combining Systems, 165-180, 2013 | 68* | 2013 |
| Infusing knowledge into the textual entailment task using graph convolutional networks P Kapanipathi, V Thost, SS Patel, S Whitehead, I Abdelaziz, ... AAAI Conference on Artificial Intelligence 34 (05), 8074-8081, 2020 | 62 | 2020 |
| Temporalizing rewritable query languages over knowledge bases S Borgwardt, M Lippmann, V Thost Journal of Web Semantics 33, 50-70, 2015 | 61 | 2015 |
| Metric temporal description logics with interval-rigid names F Baader, S Borgwardt, P Koopmann, A Ozaki, V Thost ACM Transactions on Computational Logic (TOCL) 21 (4), 1-46, 2020 | 59 | 2020 |
| Temporal query answering in the description logic EL S Borgwardt, V Thost International Joint Conference on Artificial Intelligence, 2015 | 51 | 2015 |
| A deep reinforcement learning approach to first-order logic theorem proving M Crouse, I Abdelaziz, B Makni, S Whitehead, C Cornelio, P Kapanipathi, ... AAAI Conference on Artificial Intelligence, 2019 | 48* | 2019 |
| Logic on MARS: Ontologies for Generalised Property Graphs. M Marx, M Krötzsch, V Thost International Joint Conference on Artificial Intelligence, 1188-1194, 2017 | 47 | 2017 |
| Attributed Description Logics: Reasoning on Knowledge Graphs. M Krötzsch, M Marx, A Ozaki, V Thost International Joint Conference on Artificial Intelligence, 5309-5313, 2018 | 45 | 2018 |
| Improving graph neural network representations of logical formulae with subgraph pooling M Crouse, I Abdelaziz, C Cornelio, V Thost, L Wu, K Forbus, A Fokoue arXiv preprint arXiv:1911.06904, 2019 | 44* | 2019 |
| Ontologies for knowledge graphs: Breaking the rules M Krötzsch, V Thost The Semantic Web–ISWC 2016: 15th International Semantic Web Conference, Kobe …, 2016 | 44 | 2016 |
| Data-efficient graph grammar learning for molecular generation M Guo, V Thost, B Li, P Das, J Chen, W Matusik arXiv preprint arXiv:2203.08031, 2022 | 43 | 2022 |
| Improving inductive link prediction using hyper-relational facts M Ali, M Berrendorf, M Galkin, V Thost, T Ma, V Tresp, J Lehmann The Semantic Web–ISWC 2021: 20th International Semantic Web Conference, ISWC …, 2021 | 38 | 2021 |
| Software vulnerability detection via deep learning over disaggregated code graph representation Y Zhuang, S Suneja, V Thost, G Domeniconi, A Morari, J Laredo arXiv preprint arXiv:2109.03341, 2021 | 29 | 2021 |
| Transformers over directed acyclic graphs Y Luo, V Thost, L Shi Advances in Neural Information Processing Systems 36, 2024 | 27* | 2024 |
| An Analysis of Virtual Nodes in Graph Neural Networks for Link Prediction EJ Hwang, V Thost, SS Dasgupta, T Ma The First Learning on Graphs Conference, 2022 | 26* | 2022 |
| Attributed description logics: Ontologies for knowledge graphs M Krötzsch, M Marx, A Ozaki, V Thost International Semantic Web Conference, 418-435, 2017 | 25 | 2017 |
| Temporal Query Answering in DL-Lite with Negation. S Borgwardt, V Thost Global Conference on Artificial Intelligence, 51-65, 2015 | 25 | 2015 |
Stefan BorgwardtTheoretical Computer Science, TU DresdenDirección de correo verificada de tu-dresden.de