Pasquale Minervini

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Sebastian RiedelProfessor @ University College London, Researcher @ Facebook AI ResearchVerified email at cs.ucl.ac.uk
Tim RocktäschelResearcher at DeepMind, Associate Professor at UCLVerified email at cs.ucl.ac.uk
Nicola FanizziLACAM - Dipartimento di Informatica - Università degli studi di Bari "Aldo Moro"Verified email at uniba.it
Claudia d'AmatoAssociate Professor, University of BariVerified email at uniba.it
Tim DettmersUniversity of WashingtonVerified email at cs.washington.edu
Floriana EspositoProfessore di Informatica, Università degli Studi "Aldo Moro" Bari ItalyVerified email at uniba.it
Matko BošnjakDeepMindVerified email at deepmind.com
Edward GrefenstetteHead of Machine Learning, Cohere; Honorary Professor, UCLVerified email at cohere.com
Vit NovacekFaculty of Informatics, Masaryk University / Data Science Institute, NUI GalwayVerified email at fi.muni.cz
Luca CostabelloAccenture LabsVerified email at accenture.com
Yuxiang WuUniversity College LondonVerified email at ucl.ac.uk
Thomas DemeesterAssistant professor, Ghent UniversityVerified email at ugent.be
Emir MuñozGenesys Telecommunications Laboratories, Inc.Verified email at genesys.com
Ulf LeserKnowledge Management in Bioinformatics, Humboldt-Universität zu BerlinVerified email at informatik.hu-berlin.de
Pierre-Yves VandenbusscheElsevier LabsVerified email at elsevier.com
Erik ArakelyanUCL, ARMVerified email at ucl.ac.uk
Michael CochezAssistant Professor, Vrije Universiteit AmsterdamVerified email at vu.nl
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGVerified email at dbs.ifi.lmu.de
Haim DubossarskyResearch Fellow, University of CambridgeVerified email at cam.ac.uk
Joe StaceyImperial College LondonVerified email at imperial.ac.uk

Pasquale Minervini

University College London

Verified email at cs.ucl.ac.uk - Homepage

Machine Learning Knowledge Graphs Relational Learning Natural Language Processing Reading Comprehension


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Convolutional 2d knowledge graph embeddings T Dettmers, P Minervini, P Stenetorp, S Riedel AAAI 2017, 2017	1382	2017
Adversarial sets for regularising neural link predictors P Minervini, T Demeester, T Rocktäschel, S Riedel UAI 2017, 2017	100	2017
Adversarially regularising neural nli models to integrate logical background knowledge P Minervini, S Riedel CoNLL 2018, 2018	77	2018
Differentiable Reasoning on Large Knowledge Bases and Natural Language P Minervini, M Bosnjak, T Rocktäschel, S Riedel, E Grefenstette AAAI 2020 (Oral), 125-142, 2020	74	2020
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language L Weber, P Minervini, J Münchmeyer, U Leser, T Rocktäschel ACL 2019, 2019	71	2019
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them P Lewis, Y Wu, L Liu, P Minervini, H Küttler, A Piktus, P Stenetorp, ... TACL 2021, 2021	59	2021
Knowledge Graph Embeddings and Explainable AI F Bianchi, G Rossiello, L Costabello, M Palmonari, P Minervini IOS Press, 2020	54*	2020
Regularizing knowledge graph embeddings via equivalence and inversion axioms P Minervini, L Costabello, E Muñoz, V Nováček, PY Vandenbussche Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017	46	2017
NeurIPS 2020 EfficientQA competition: Systems, analyses and lessons learned S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ... Proceedings of the NeurIPS 2020 Competition and Demonstration Track, PMLR …, 2021	42	2021
Towards neural theorem proving at scale P Minervini, M Bosnjak, T Rocktäschel, S Riedel arXiv preprint arXiv:1807.08204, 2018	41	2018
Learning Reasoning Strategies in End-to-End Differentiable Proving P Minervini, S Riedel, P Stenetorp, E Grefenstette, T Rocktäschel ICML 2020, 2020	40	2020
Make up your mind! Adversarial generation of inconsistent natural language explanations OM Camburu, B Shillingford, P Minervini, T Lukasiewicz, P Blunsom ACL 2019, 2019	40	2019
Complex Query Answering with Neural Link Predictors E Arakelyan, D Daza, P Minervini, M Cochez ICLR 2021 (Oral, Outstanding Paper Award), 2021	39	2021
Can real-time machine translation overcome language barriers in distributed requirements engineering? F Calefato, F Lanubile, P Minervini 2010 5th IEEE International Conference on Global Software Engineering, 257-264, 2010	27	2010
Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models DV Manela, D Errington, T Fisher, B van Breugel, P Minervini EACL 2021 (Oral), 2021	24*	2021
Avoiding the hypothesis-only bias in natural language inference via ensemble adversarial training J Stacey, P Minervini, H Dubossarsky, S Riedel, T Rocktäschel EMNLP 2020, 2020	21*	2020
Scalable learning of entity and predicate embeddings for knowledge graph completion P Minervini, N Fanizzi, C d'Amato, F Esposito 2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015	17	2015
Extrapolation in NLP J Mitchell, P Minervini, P Stenetorp, S Riedel arXiv preprint arXiv:1805.06648, 2018	15	2018
Leveraging the schema in latent factor models for knowledge graph completion P Minervini, C d'Amato, N Fanizzi, F Esposito Proceedings of the 31st annual ACM symposium on applied computing, 327-332, 2016	15	2016
Efficient energy-based embedding models for link prediction in knowledge graphs P Minervini, C d’Amato, N Fanizzi Journal of Intelligent Information Systems 47 (1), 91-109, 2016	14	2016

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