neuralnoise.com

Selected Grants as PI

CLARIFY, Cancer Long Survivors Artificial Intelligence Follow Up. Funded under H2020-EU.3.1.5.1, H2020-EU.3.1.3.2. Topics: SC1-DTH-01-2019 - Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment.
Gradient-based Learning of Complex Latent Structures. Funded under the Edinburgh Laboratory for Integrated Artificial Intelligence (ELIAI).

Patents

Minervini, Costabello, Muñoz, Nováček, Vandenbussche - Method and Apparatus for Completing a Knowledge Graph. United States Patent: US11341417B2, Japan Patent: JP6954049B2, Current Assignee: Fujitsu Ltd.

Tutorials

Lecue, Giannotti, Guidotti, Minervini - On Explainable AI: From Theory to Motivation, Industrial Applications, XAI Coding & Engineering Practices. Tutorial for the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)
Lecue, Giannotti, Guidotti, Minervini - On Explainable AI: From Theory to Motivation, Industrial Applications, XAI Coding & Engineering Practices. Tutorial for the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022)
Lecue, Minervini, Giannotti, Guidotti - On Explainable AI: From Theory to Motivation, Industrial Applications and Coding Practices. Tutorial for the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021)
Lecue, Gade, Geyik, Kenthapadi, Mithal, Taly, Guidotti, Minervini - On Explainable AI: Foundations, Industrial Applications, Practical Challenges, and Lessons Learned. Tutorial for the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
Costabello, Lecue, Giannotti, Guidotti, Hitzler, Minervini, Sarker - On Explainable AI: From Theory to Motivation, Applications and Limitations. Half-day (3.5 hours) Tutorial for the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019)
Guidotti, Minervini, Monreale, Rinzivillo - Tutorial on Explainable Knowledge Discovery in Data Mining. Tutorial for the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2019)
Riedel, Minervini - Differentiable Program Interpreters. Lecture at the Summer School on Statistical Relational Artificial Intelligence (ACAI 2018)

Publications

Minervini, Franceschi, Niepert - Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. 37th AAAI Conference on Artificial Intelligence (AAAI 2023, 19.6% acceptance rate) [bibtex]
Arakelyan*, Minervini*, Daza, Cochez, Augenstein - Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. 37th Conference on Neural Information Processing Systems (NeurIPS 2023, 26% acceptance rate) [bibtex]
Kaddour, Key, Nawrot, Minervini, Kusner - No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. 37th Conference on Neural Information Processing Systems (NeurIPS 2023, 26% acceptance rate) [bibtex]
Andresel, Tran, Domokos, Minervini, Stepanova - Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs. 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023) [bibtex]
Zhou, Iacobacci, Minervini - XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking. The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023) [bibtex]
Janik, Torrente, Costabello, Calvo, Walsh, Camps, Mohamed, Ortega, Nováček, Massutí, Minervini, Garcia Campelo, Del Barco, Bosch-Barrera, Menasalvas, Timilsina, Provencio - Machine Learning–Assisted Recurrence Prediction for Patients With Early-Stage Non–Small-Cell Lung Cancer. JCO Clinical Cancer Informatics 2023 :7 [export citation]
Timilsina, Fey, Buosi, Janik, Costabello, Carcereny, Rodrıguez Abreu, Cobo, López Castro, Bernabé, Minervini, Torrente, Provencio, Nováček - Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer. Journal of Biomedical Informatics 144, ISSN 1532-0464 [bibtex]
Timilsina, Buosi, Janik, Minervini, Costabello, Torrente, Provencio, Calvo, Camps, Ortega, Massutí, Garcia Campelo, del Barco Bosch-Barrera, Nováček - Learning Survival Models for Relapse Prediction in Early-Stage Lung Cancer Patients. International Joint Conference on Neural Networks (IJCNN 2023) [bibtex]
Cochez, Alivanistos, Arakelyan, Berrendorf, Daza, Galkin, Minervini, Niepert, Ren - Approximate Answering of Graph Queries. Chapter in Compendium of Neurosymbolic Artificial Intelligence, IOS Press (2023). [bibtex]
Dileo, Minervini, Zignani, Gaito - Temporal Smoothness Regularisers for Neural Link Predictors. CoRR abs/2309.09045 (2023) [bibtex]
Gema, Daines, Minervini, Alex - Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain. CoRR abs/2307.03042 (2023) [bibtex]
Solano, Camburu, Minervini - SparseFit: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations. CoRR abs/2305.13235 (2023) [bibtex]
Stacey, Minervini, Dubossarsky, Camburu, Rei - Logical Reasoning for Natural Language Inference Using Generated Facts as Atoms. CoRR abs/2305.13214 (2023) [bibtex]
Gema, Grabarczyk, De Wulf, Borole, Alfaro, Minervini, Vergari, Rajan - Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks. CoRR abs/2305.19979 (2023) [bibtex]
Chen, Mishra, Franceschi, Minervini, Stenetorp, Riedel - ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. 36th Conference on Neural Information Processing Systems (NeurIPS 2022) [bibtex]
Stacey, Minervini, Dubossarsky, Rei - Logical Reasoning with Span Predictions: Span-level Logical Atoms for Interpretable and Robust NLI Models. 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022) and Efficient Natural Language and Speech Processing Workshop (ENLSP @ NeurIPS 2022, best poster award) [bibtex]
Wu, Zhao, Hu, Minervini, Stenetorp, Riedel - An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks. 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)
Amin*, Minervini*, Chang, Stenetorp, Neumann - MedDistant19: Towards an Accurate Benchmark for Broad-Coverage Biomedical Relation Extraction. 29th International Conference on Computational Linguistics (COLING 2022) [bibtex]
Minervini*, Arakelyan*, Daza*, Cochez - Complex Query Answering with Neural Link Predictors (Extended Abstract). 31st International Joint Conference on Artificial Intelligence (IJCAI 2022) [bibtex]
Morris, Minervini, Blunsom - Learning Proof Path Selection Policies in Neural Theorem Proving. 16th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy @ IJCLR 2022), and 4th Conference on Automated Knowledge Base Construction (AKBC 2022) [bibtex]
Wren, Minervini, Franceschi, Zantedeschi - Learning Discrete Directed Acyclic Graphs via Backpropagation. Workshop on Causality for Real-world Impact (CML4Impact @ NeurIPS 2022), and Workshop on Neuro Causal and Symbolic AI (nCSI @ NeurIPS 2022) [bibtex]
Arakelyan*, Daza*, Minervini*, Cochez - Complex Query Answering with Neural Link Predictors. 9th International Conference on Learning Representations (ICLR 2021, oral presentation 2% acceptance rate, overall 29% - Outstanding Paper Award) [bibtex, presentation]
Niepert, Minervini, Franceschi - Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. 35th Conference on Neural Information Processing Systems (NeurIPS 2021) [bibtex, presentation, Yannic Kilcher's explanation]
Jiang, Minervini, Jiang, Rocktäschel - Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021, 24.8% acceptance rate, oral presentation) [bibtex]
Lewis, Wu, Liu, Minervini, Küttler, Piktus, Stenetorp, Riedel - PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them. Transactions of the Association for Computational Linguistics (TACL 2021) [bibtex, presentation]
Wu, Minervini, Stenetorp, Riedel - Training Adaptive Computation for Open-Domain Question Answeringwith Computational Constraints. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) [bibtex]
de Vassimon Manela, Errington, Fisher, van Breugel, Minervini - Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models. 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021) [bibtex]
Dobrowolska, Vergari, Minervini - Neural Concept Formation in Knowledge Graphs. 3rd International Conference on Automated Knowledge Base Construction (AKBC 2021)
Chen, Minervini, Stenetorp, Riedel - Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations. 3rd International Conference on Automated Knowledge Base Construction (AKBC 2021)
Mohamed, Walsh, Timilsina, Torrente, Franco, Provencio, Janik, Costabello, Minervini, Stenetorp, Novácek - On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. American Medical Informatics Association, Annual Symposium (AMIA 2021)
Torrente, Franco, Calvo, Collazo Lorduy, Menasalvas, Vidal, Sousa, Pimentao, Novacek, Minervini, Fey, Costabello, Pocs, Provencio - P08.01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together. Journal of Thoracic Oncology, International Association for the Study of Lung Cancer 16(10):S991-S992, October 2021
Chauhan, Gupta, Minervini - A Probabilistic Framework for Knowledge Graph Data Augmentation. Data-Centric AI Workshop (DCAI @ NeurIPS 2021)
Betz, Niepert, Minervini, Stuckenschmidt - Backpropagating through Markov Logic Networks. Proceedings of 15th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2020/2021 @ IJCLR 2021)
Minervini, Riedel, Stenetorp, Grefenstette, Rocktäschel - Learning Reasoning Strategies in End-to-End Differentiable Proving. 37th International Conference on Machine Learning (ICML 2020, 21.8% acceptance rate) [bibtex]
Minervini*, Bošnjak*, Rocktäschel, Riedel, Grefenstette - Differentiable Reasoning on Large Knowledge Bases and Natural Language. 34th AAAI Conference on Artificial Intelligence (AAAI 2020, oral presentation 4.5% acceptance rate; overall 20.6%) [bibtex]
Min, Boyd-Graber, Alberti, Chen, Choi, Collins, Guu, Hajishirzi, Lee, Palomaki, Raffel, Roberts, Kwiatkowski, Lewis, Wu, Küttler, Liu, Minervini, Stenetorp, Riedel, Yang, Seo, Izacard, Petroni, Hosseini, De Cao, Grave, Yamada, Shimaoka, Suzuki, Miyawaki, Sato, Takahashi, Suzuki, Fajcik, Docekal, Ondrej, Smrz, Cheng, Shen, Liu, He, Chen, Gao, Oguz, Chen, Karpukhin, Peshterliev, Okhonko, Schlichtkrull, Gupta, Mehdad, Yih - NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS 2020 Competition and Demonstration Track (NeurIPS 2020) [bibtex]
Camburu, Shillingford, Minervini, Lukasiewicz, Blunsom - Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020, 17.6% acceptance rate) [bibtex]
Wu, Minervini, Stenetorp, Riedel - Don't Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020, 22.4% acceptance rate) [bibtex]
Stacey, Minervini, Dubossarsky, Riedel, Rocktäschel - Gone At Last: Removing the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020, 22.4% acceptance rate) [bibtex]
Welbl, Minervini, Bartolo, Stenetorp, Riedel - Undersensitivity in Neural Reading Comprehension. Findings of EMNLP 2020 [bibtex]
Minervini, Bošnjak, Rocktäschel, Riedel, Grefenstette - Differentiable Reasoning on Large Knowledge Bases and Natural Language. Chapter in Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges, IOS Press (2020). [bibtex]
Bianchi, Rossiello, Costabello, Palmonari, Minervini - Knowledge Graph Embeddings and Explainable AI. Chapter in Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges, IOS Press (2020). [bibtex]
Dobrowolska, Vergari, Minervini - Neural Concept Formation in Knowledge Graphs. Knowledge Representation & Reasoning Meets Machine Learning workshop at NeurIPS (KR2ML 2020)
Stacey, Minervini, Dubossarsky, Riedel, Rocktäschel - There is Strength in Numbers: Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adver-sarial Training. CoRR abs/2004.07790 (2020)
Jiang, Luketina, Nardelli, Minervini, Torr, Whiteson, Rocktäschel - WordCraft: An Environment for Benchmarking Commonsense Agents. Workshop on Language in Reinforcement Learning (LaReL) @ ICML 2020 [bibtex]
Camburu, Shillingford, Minervini, Lukasiewicz, Blunsom - Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. NeurIPS 2019 Workshop on Safety and Robustness in Decision Making (Safe Robust @ NeurIPS, 2019) [bibtex]
Weber, Minervini, Münchmeyer, Leser, Rocktäschel - NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language. 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019, 22.7% acceptance rate) [bibtex]
Muñoz, Minervini, Nickles - Embedding Cardinality Constraints in Neural Link Predictors. ACM Symposium on Applied Computing - Semantic Web Track (ACM SAC 2019, 25% acceptance rate) [bibtex]
Cowen-Rivers, Minervini, Riedel, Rocktäschel, Wang, Bošnjak - Neural Variational Inference for Estimating Knowledge Graph Embedding Uncertainty. 14th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy) at IJCAI 2019 [bibtex]
Minervini, Riedel - Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge. SIGNLL Conference on Computational Natural Language Learning (CoNLL 2018, 20.65% acceptance rate) [bibtex]
Minervini, Bošnjak, Campero, Rocktäschel, Grefenstette, Riedel - Neural Theorem Proving on Natural Language. International Conference on Probabilistic Programming (PROBPROG 2018)
Minervini, Bošnjak, Rocktäschel, Riedel - Towards Neural Theorem Proving at Scale. Federated Artificial Intelligence Meeting (FAIM) Workshop on Neural Abstract Machines & Program Induction v2 (NAMPI 2018) [bibtex]
Mitchell, Minervini, Stenetorp, Riedel - Extrapolation in NLP. Workshop on Generalization in the Age of Deep Learning @ ACL 2018 [bibtex]
Weissenborn, Minervini, Dettmers, Augenstein, Welbl, Rocktäschel, Bošnjak, Mitchell, Demeester, Stenetorp, Riedel - Jack the Reader - A Machine Reading Framework. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2018), System Demonstrations [bibtex]
Dettmers, Minervini, Stenetorp, Riedel - Convolutional 2D Knowledge Graph Embeddings. 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), February 2018 [bibtex]
Minervini, Tresp, d'Amato, Fanizzi - Adaptive Knowledge Propagation in Web Ontologies. Journal Article on ACM Transactions on the Web (ACM TWEB 2018) [bibtex]
Minervini, Demeester, Rocktäschel, Riedel - Adversarial Sets for Regularising Neural Link Predictors. 33rd Conference on Uncertainty in Artificial Intelligence (UAI 2017), August 2017 [bibtex]
Minervini, Costabello, Muñoz, Nováček, Vandenbussche - Regularizing Neural Knowledge Graph Embeddings via Equivalence and Inversion Axioms. European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017) [bibtex]
Minervini, d'Amato, Fanizzi - Efficient Energy-based Embedding Models for Link Prediction in Knowledge Graphs. Journal on Intelligent Information Systems (JIIS 2016), Recent Advances in Mining Patterns from Complex Data, ISSN 1573-7675, June 2016 [bibtex]
Minervini, d'Amato, Fanizzi, Tresp - Discovering Similarity and Dissimilarity Relations for Knowledge Propagation in Web Ontologies. Journal on Data Semantics (JoDS), May 2016 [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Leveraging the Schema in Latent Factor Models for Knowledge Graph Completion. ACM Symposium on Applied Computing - Semantic Web Track (ACM SAC 2016), ISBN 978-1-4503-3739-7, April 2016 (24% acceptance rate) [bibtex]
Yumusak, Muñoz, Minervini, Dogdu, Kodaz - A Hybrid Method for Rating Prediction Using Linked Data Features and Text Reviews. 1st International Workshop on Completing and Debugging the Semantic Web (Know@LOD-2016 (winning entry) [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Scalable Learning of Entity and Predicate Embeddings for Knowledge Graph Completion. 14th IEEE International Conference on Machine Learning and Applications (ICMLA 2015), ISBN 978-1-5090-0287-0, December 2015 [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Efficient Learning of Entity and Predicate Embeddings for Link Prediction in Knowledge Graphs. 11th International Workshop on Uncertainty Reasoning for the Semantic Web, October 2015 [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - A Gaussian Process Model for Knowledge Propagation in Web Ontologies. IEEE International Conference on Data Mining (ICDM 2014) ISBN 978-1-4799-4302-9, December 2014 (19% acceptance rate) [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Adaptive Knowledge Propagation in Web Ontologies. 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014), ISBN 978-3-319-13703-2, November 2014 (best paper award) [bibtex]
Minervini, d'Amato, Fanizzi, Tresp - Learning to Propagate Knowledge in Web Ontologies. 10th International Workshop on Uncertainty Reasoning for the Semantic Web (best paper award) [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Graph-Based Regularization for Transductive Class-Membership Prediction. In: Uncertainty Reasoning for the Semantic Web III - ISWC International Workshops, URSW 2011-2013, Revised Selected Papers - Springer, ISBN: 978-3-319-13412-3 [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Learning Probabilistic Description Logic Concepts Under Alternative Assumptions on Incompleteness. In: Uncertainty Reasoning for the Semantic Web III - ISWC International Workshops, URSW 2011-2013, Revised Selected Papers - Springer, ISBN: 978-3-319-13412-3 [bibtex]
Minervini, Fanizzi, d'Amato, Esposito - Rank Prediction for Semantically Annotated Resources. ACM Symposium on Applied Computing - Semantic Web Track (ACM SAC 2013), ISBN 978-1-4503-1656-9, March 2013 (24% acceptance rate) [bibtex]
Minervini, d'Amato, Fanizzi, Esposito - Transductive Inference for Class-Membership Propagation in Web Ontologies. The Semantic Web: Semantics and Big Data (ESWC 2013), ISBN 978-3-642-38287-1, May 2013 (26% acceptance rate) (sources and datasets) [bibtex]
Minervini, Fanizzi, d'Amato, Esposito - Learning probabilistic Description logic concepts: under different Assumptions on missing knowledge. ACM Symposium on Applied Computing - Semantic Web Track (ACM SAC 2012), ISBN 978-1-4503-0857-1, March 2012 [bibtex]
Minervini, d'Amato, Fanizzi - A Graph Regularization Based Approach to Transductive Class-Membership Prediction. 8th International Workshop on Uncertainty Reasoning for the Semantic Web, November 2012 [bibtex]
Fanizzi, d’Amato, Esposito, Minervini - Numeric Prediction on OWL Knowledge Bases through Terminological Regression Trees. International Journal on Semantic Computing 2012 [bibtex]
Minervini, d'Amato, Fanizzi - Learning Terminological Bayesian Classifiers: A Comparison of Alternative Approaches to Dealing with Unknown Concept Memberships. 9th Italian Convention on Computational Logic, June 2012 [bibtex]
Minervini, d'Amato, Fanizzi - Learning Terminological Naive Bayesian Classifiers under Different Assumptions on Missing Knowledge. 7th International Workshop on Uncertainty Reasoning for the Semantic Web (URSW 2011), CEUR Workshop Proceedings vol. 778 ISSN 1613-0073, October 2011 [bibtex]
Calefato, Lanubile, Minervini - Can Real-Time Machine Translation Overcome Language Barriers in Distributed Requirements Engineering?. 5th IEEE International Conference on Global Software Engineering, IEEE ICGSE 2010, ISBN 978-1-4244-7619-0, August 2010 [bibtex]
Minervini - Apertium goes SOA: an efficient and scalable service based on the Apertium rule-based machine translation platform. 1st International Workshop on Free/Open-Source Rule-Based Machine Translation, ISBN-13: 978-8-46-136188-5, November 2009