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ORCIDDavide Mottin
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- affiliation: Aarhus University, Denmark
- affiliation (former): Hasso Plattner Institute, Potsdam, Germany
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2020 – today
- 2024
[c33]Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin:
Harnessing Large Language Models as Post-hoc Correctors. ACL (Findings) 2024: 14559-14574- [c32]Juan Manuel Rodriguez
, Nima Tavassoli, Eliezer Levy, Gil Lederman, Dima Sivov, Matteo Lissandrini, Davide Mottin:
Does the Performance of Text-to-Image Retrieval Models Generalize Beyond Captions-as-a-Query? ECIR (4) 2024: 161-176 - [c31]Cheng Huang, Alexander Mathiasen, Josef Dean, Davide Mottin, Ira Assent:
HUNIPU: Efficient Hungarian Algorithm on IPUs. ICDEW 2024: 388-394 - [c30]Zhiqiang Zhong, Davide Mottin:
Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding. ECML/PKDD (7) 2024: 399-415 - [c29]Maximilian K. Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras, Ilaria Bordino, Francesco Gullo, Aris Anagnostopoulos:
ReliK: A Reliability Measure for Knowledge Graph Embeddings. SEBD 2024: 80-90 - [c28]Maximilian K. Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras, Ilaria Bordino, Francesco Gullo, Aris Anagnostopoulos:
ReliK: A Reliability Measure for Knowledge Graph Embeddings. WWW 2024: 2009-2019 - [i25]Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin:
Harnessing Large Language Models as Post-hoc Correctors. CoRR abs/2402.13414 (2024) - [i24]Zhiqiang Zhong, Davide Mottin:
EvolMPNN: Predicting Mutational Effect on Homologous Proteins by Evolution Encoding. CoRR abs/2402.13418 (2024) - [i23]Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin:
Benchmarking Large Language Models for Molecule Prediction Tasks. CoRR abs/2403.05075 (2024) - [i22]Steinn Ymir Agustsson, Alfred J. H. Jones, Davide Curcio, Søren Ulstrup, Jill Miwa, Davide Mottin, Panagiotis Karras, Philip Hofmann:
Autonomous microARPES. CoRR abs/2403.13815 (2024) - [i21]Maximilian K. Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras, Ilaria Bordino, Francesco Gullo, Aris Anagnostopoulos:
ReliK: A Reliability Measure for Knowledge Graph Embeddings. CoRR abs/2404.16572 (2024) - [i20]Saeedeh Javadi, Atefeh Moradan, Mohammad Sorkhpar, Klim Zaporojets, Davide Mottin, Ira Assent:
Wiki Entity Summarization Benchmark. CoRR abs/2406.08435 (2024) - [i19]Steinn Ymir Agustsson, Mohammad Ahsanul Haque, Tam T. Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras, Philip Hofmann:
An autoencoder for compressing angle-resolved photoemission spectroscopy data. CoRR abs/2407.04631 (2024) - [i18]Zhiqiang Zhong, Davide Mottin:
Exploring Graph Structure Comprehension Ability of Multimodal Large Language Models: Case Studies. CoRR abs/2409.08864 (2024) - 2023
- [j14]Atefeh Moradan, Andrew Draganov, Davide Mottin, Ira Assent:
UCoDe: unified community detection with graph convolutional networks. Mach. Learn. 112(12): 5057-5080 (2023) - [j13]Kasper Overgaard Mortensen, Fatemeh Zardbani, Mohammad Ahsanul Haque, Steinn Ymir Agustsson, Davide Mottin, Philip Hofmann, Panagiotis Karras:
Marigold: Efficient k-means Clustering in High Dimensions. Proc. VLDB Endow. 16(7): 1740-1748 (2023) - [j12]Judith Hermanns, Konstantinos Skitsas, Anton Tsitsulin, Marina Munkhoeva, Alexander Frederiksen Kyster, Simon Nielsen, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Scalable Graph Alignment by Spectral Corresponding Functions. ACM Trans. Knowl. Discov. Data 17(4): 50:1-50:26 (2023) - [c27]Konstantinos Skitsas, Karol Orlowski, Judith Hermanns, Davide Mottin, Panagiotis Karras:
Comprehensive Evaluation of Algorithms for Unrestricted Graph Alignment. EDBT 2023: 260-272 - [c26]Andrew Draganov, Jakob Rødsgaard Jørgensen, Katrine Scheel, Davide Mottin, Ira Assent, Tyrus Berry, Çigdem Aslay:
ActUp: Analyzing and Consolidating tSNE and UMAP. IJCAI 2023: 3651-3658 - [c25]Zhiqiang Zhong, Davide Mottin:
Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability. KDD 2023: 5841-5842 - [c24]Ama Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, Panagiotis Karras:
Spectral Subgraph Localization. LoG 2023: 7 - [i17]Zhiqiang Zhong, Anastasia Barkova, Davide Mottin:
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability. CoRR abs/2302.08261 (2023) - [i16]Andrew Draganov, Jakob Rødsgaard Jørgensen, Katrine Scheel Nellemann, Davide Mottin, Ira Assent, Tyrus Berry, Çigdem Aslay:
ActUp: Analyzing and Consolidating tSNE and UMAP. CoRR abs/2305.07320 (2023) - [i15]Marc Christiansen, Lea Villadsen, Zhiqiang Zhong, Stefano Teso, Davide Mottin:
How Faithful are Self-Explainable GNNs? CoRR abs/2308.15096 (2023) - [i14]Zhiqiang Zhong, Yangqianzi Jiang, Davide Mottin:
On the Robustness of Post-hoc GNN Explainers to Label Noise. CoRR abs/2309.01706 (2023) - 2022
- [c23]Matteo Lissandrini, Davide Mottin, Katja Hose, Torben Bach Pedersen:
Knowledge Graph Exploration Systems: are we lost? CIDR 2022 - [i13]Andrew Draganov, Tyrus Berry, Jakob Rødsgaard Jørgensen, Katrine Scheel Nellemann, Ira Assent, Davide Mottin:
GiDR-DUN; Gradient Dimensionality Reduction - Differences and Unification. CoRR abs/2206.09689 (2022) - [i12]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. CoRR abs/2211.01434 (2022) - 2021
- [j11]Giulia Preti, Matteo Lissandrini, Davide Mottin, Yannis Velegrakis:
Mining patterns in graphs with multiple weights. Distributed Parallel Databases 39(2): 281-319 (2021) - [j10]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Anytime Graph Embeddings. Proc. VLDB Endow. 14(6): 1102-1110 (2021) - [c22]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment Through Spectral Signatures. APWeb/WAIM (1) 2021: 44-52 - [c21]Alexander Frederiksen Kyster, Simon Daugaard Nielsen, Judith Hermanns, Davide Mottin, Panagiotis Karras:
Boosting Graph Alignment Algorithms. CIKM 2021: 3166-3170 - [c20]Georgia Troullinou, Haridimos Kondylakis, Matteo Lissandrini, Davide Mottin:
SOFOS: Demonstrating the Challenges of Materialized View Selection on Knowledge Graphs. SIGMOD Conference 2021: 2789-2793 - [c19]Michael Loster, Davide Mottin, Paolo Papotti, Jan Ehmüller, Benjamin Feldmann, Felix Naumann:
Few-Shot Knowledge Validation using Rules. WWW 2021: 3314-3324 - [e3]Davide Mottin, Matteo Lissandrini, Senjuti Basu Roy, Yannis Velegrakis:
Proceedings of the 2nd Workshop on Search, Exploration, and Analysis in Heterogeneous Datastores (SEA-Data 2021) co-located with 47th International Conference on Very Large Data Bases (VLDB 2021), Copenhagen, Denmark, August 20, 2021. CEUR Workshop Proceedings 2929, CEUR-WS.org 2021 [contents] - [i11]Freya Behrens, Stefano Teso, Davide Mottin:
Bandits for Learning to Explain from Explanations. CoRR abs/2102.03815 (2021) - [i10]Georgia Troullinou, Haridimos Kondylakis, Matteo Lissandrini, Davide Mottin:
SOFOS: Demonstrating the Challenges of Materialized View Selection on Knowledge Graphs. CoRR abs/2103.06531 (2021) - [i9]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment through Spectral Signatures. CoRR abs/2106.05729 (2021) - [i8]Atefeh Moradan, Andrew Draganov, Davide Mottin, Ira Assent:
UCoDe: Unified Community Detection with Graph Convolutional Networks. CoRR abs/2112.14822 (2021) - 2020
- [j9]Matteo Lissandrini, Torben Bach Pedersen, Katja Hose, Davide Mottin:
Knowledge graph exploration: where are we and where are we going? SIGWEB Newsl. 2020(Summer): 4:1-4:8 (2020) - [c18]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
The Shape of Data: Intrinsic Distance for Data Distributions. ICLR 2020 - [c17]Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin:
What if Neural Networks had SVDs? NeurIPS 2020 - [c16]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis:
Graph-Query Suggestions for Knowledge Graph Exploration. WWW 2020: 2549-2555 - [e2]Alexandra Poulovassilis, David Auber, Nikos Bikakis, Panos K. Chrysanthis, George Papastefanatos, Mohamed A. Sharaf, Nikos Pelekis, Chiara Renso, Yannis Theodoridis, Karine Zeitouni, Tania Cerquitelli, Silvia Chiusano, Genoveva Vargas-Solar, Behrooz Omidvar-Tehrani, Katharina Morik, Jean-Michel Renders, Donatella Firmani, Letizia Tanca, Davide Mottin, Matteo Lissandrini, Yannis Velegrakis:
Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, Copenhagen, Denmark, March 30, 2020. CEUR Workshop Proceedings 2578, CEUR-WS.org 2020 [contents] - [i7]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Linear-Space Anytime Graph Embeddings. CoRR abs/2006.04746 (2020) - [i6]Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin:
What if Neural Networks had SVDs? CoRR abs/2009.13977 (2020)
2010 – 2019
- 2019
- [c15]Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller, Danai Koutra:
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket. ICDM 2019: 528-537 - [c14]Nikita Klyuchnikov, Davide Mottin, Georgia Koutrika, Emmanuel Müller, Panagiotis Karras:
Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging. KDD 2019: 686-695 - [c13]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis:
Example-based Search: a New Frontier for Exploratory Search. SIGIR 2019: 1411-1412 - [c12]Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas:
Exploring the Data Wilderness through Examples. SIGMOD Conference 2019: 2031-2035 - [c11]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. WWW (Companion Volume) 2019: 308-309 - [r1]Davide Mottin, Yinghui Wu:
Graph Exploration and Search. Encyclopedia of Big Data Technologies 2019 - [i5]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
Intrinsic Multi-scale Evaluation of Generative Models. CoRR abs/1905.11141 (2019) - 2018
- [b2]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis:
Data Exploration Using Example-Based Methods. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2018, ISBN 978-3-031-00738-5 - [j8]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis:
X2Q: Your Personal Example-based Graph Explorer. Proc. VLDB Endow. 11(12): 2026-2029 (2018) - [c10]Giulia Preti, Matteo Lissandrini, Davide Mottin, Yannis Velegrakis:
Beyond Frequencies: Graph Pattern Mining in Multi-weighted Graphs. EDBT 2018: 169-180 - [c9]Davide Mottin, Bastian Grasnick, Axel Kroschk, Patrick Siegler, Emmanuel Müller:
Notable Characteristics Search through Knowledge Graphs. EDBT 2018: 429-432 - [c8]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis:
Multi-Example Search in Rich Information Graphs. ICDE 2018: 809-820 - [c7]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. KDD 2018: 2347-2356 - [c6]Freya Behrens, Sebastian Bischoff, Pius Ladenburger, Julius Rückin, Laurenz Seidel, Fabian Stolp, Michael Vaichenker, Adrian Ziegler, Davide Mottin, Fatemeh Aghaei, Emmanuel Müller, Martin Preusse, Nikola Müller, Michael Hunger:
MetaExp: Interactive Explanation and Exploration of Large Knowledge Graphs. WWW (Companion Volume) 2018: 199-202 - [c5]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. WWW 2018: 539-548 - [i4]Davide Mottin, Bastian Grasnick, Axel Kroschk, Patrick Siegler, Emmanuel Müller:
Notable Characteristics Search through Knowledge Graphs. CoRR abs/1802.04060 (2018) - [i3]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. CoRR abs/1803.04742 (2018) - [i2]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. CoRR abs/1805.10712 (2018) - [i1]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
SGR: Self-Supervised Spectral Graph Representation Learning. CoRR abs/1811.06237 (2018) - 2017
- [j7]Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas:
New Trends on Exploratory Methods for Data Analytics. Proc. VLDB Endow. 10(12): 1977-1980 (2017) - [c4]Davide Mottin, Emmanuel Müller:
Graph Exploration: From Users to Large Graphs. SIGMOD Conference 2017: 1737-1740 - 2016
- [j6]Davide Mottin, Alice Marascu, Senjuti Basu Roy, Gautam Das, Themis Palpanas, Yannis Velegrakis:
A holistic and principled approach for the empty-answer problem. VLDB J. 25(4): 597-622 (2016) - [j5]Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas:
Exemplar queries: a new way of searching. VLDB J. 25(6): 741-765 (2016) - [e1]Ralf Krestel, Davide Mottin, Emmanuel Müller:
Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", Potsdam, Germany, September 12-14, 2016. CEUR Workshop Proceedings 1670, CEUR-WS.org 2016 [contents] - 2015
- [b1]Davide Mottin:
Advanced Query Paradigms for the Novice User. University of Trento, Italy, 2015 - [c3]Davide Mottin, Francesco Bonchi, Francesco Gullo:
Graph Query Reformulation with Diversity. KDD 2015: 825-834 - 2014
- [j4]Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas:
Exemplar Queries: Give me an Example of What You Need. Proc. VLDB Endow. 7(5): 365-376 (2014) - [j3]Matteo Lissandrini, Davide Mottin, Themis Palpanas, Dimitra Papadimitriou, Yannis Velegrakis:
Unleashing the Power of Information Graphs. SIGMOD Rec. 43(4): 21-26 (2014) - [c2]Davide Mottin, Matteo Lissandrini, Yannis Velegrakis, Themis Palpanas:
Searching with XQ: the exemplar query search engine. SIGMOD Conference 2014: 901-904 - [c1]Davide Mottin, Alice Marascu, Senjuti Basu Roy, Gautam Das, Themis Palpanas, Yannis Velegrakis:
IQR: an interactive query relaxation system for the empty-answer problem. SIGMOD Conference 2014: 1095-1098 - 2013
- [j2]Davide Mottin, Themis Palpanas, Yannis Velegrakis:
Entity ranking using click-log information. Intell. Data Anal. 17(5): 837-856 (2013) - [j1]Davide Mottin, Alice Marascu, Senjuti Basu Roy, Gautam Das, Themis Palpanas, Yannis Velegrakis:
A Probabilistic Optimization Framework for the Empty-Answer Problem. Proc. VLDB Endow. 6(14): 1762-1773 (2013)
Coauthor Index
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