Nature-Inspired Machine Intelligence (NIMI)2023-02-10T15:13:41+01:00
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NIMI
Nature-Inspired Machine Intelligence
Full 2
Nature-Inspired Machine Learning

NIMI | InfAI

Nature-Inspired Machine Intelligence

Nature, and all that it encompasses, has influenced computer science, in particular Artificial Intelligence, from its inception. Many effective tools, mechanisms, processes, algorithms, methods, and systems have been proposed inspired by nature. For example, Neural Networks are roughly inspired by the cognitive brain function, Genetic Algorithms are inspired by evolution and the survival of the fittest, and Artificial Immune Systems are inspired by their biological equivalents. Further examples include swarm or collective approaches, that are inspired by colonies of insects and birds. Current AI methods have the following weaknesses:

  1. The power efficiency of AI systems is very low — a brain just needs a few watts compared to supercomputer/clouds, and
  2. Systems are often low-level end-to-end and cannot incorporate knowledge very well, however, most of the intelligence of humans comes from building layer after layer of knowledge
  3. Systems often lack the robustness and lifelong learning abilities we see in nature

„The job of a scientist is to listen carefully to nature, not to tell nature how to behave.“

Richard P. Feynman

Research in machine intelligence inspired by natural science can result in innovations that address those weaknesses. The main activities of the group and planned research directions will focus on existing concepts in nature and natural science including intelligent systems such as the human brain. Within the group, the following focal points will be addressed in the next years:

  • Nature in Knowledge Representation — Representation Learning and Reasoning
  • Natural Sciences in Knowledge Discovery and Data Mining with Embeddings/Neural Networks
  • Human Mind in Deep Neural-symbolic Learning and Reasoning
  • Nature-inspired Neural Networks
  • Applications of Machine Intelligence for Social good, Scholarly Communication and Education, Health, and  Nature and Environmental Studies 

MEET NIMI TEAM

Dr. Sahar Vahdati
Dr. Sahar VahdatiGroup Leader
at NIMI | InfAI
Mirza Mohtashim Alam
Mirza Mohtashim AlamResearch Associate
at NIMI | InfAI
Kossi Amouzouvi
Kossi AmouzouviSenior Researcher
at NIMI | InfAI
Saleem Muhammad
Saleem MuhammadSenior Researcher
at NIMI | InfAI
Mehdi Azarafza
Mehdi AzarafzaResearch Associate
at NIMI | InfAI
Bowen Song
Bowen SongResearch Associate
at NIMI | InfAI
Jason Li
Jason LiResearch Associate
at NIMI | InfAI
Nikhil Ostwal
Nikhil Ostwal Research Associate
at NIMI | InfAI
Qasid Saleem
Qasid SaleemStudent assistant
at NIMI | InfAI
Prathmesh Dudhe
Prathmesh DudheStudent assistant
at NIMI | InfAI
Abrar Hyder Mohammed
Abrar Hyder MohammedStudent assistant
at NIMI | InfAI

SELECTED PUBLICATIONS

5* Knowledge Graph Embeddings with Projective Transformations

Nayyeri, Mojtaba; Vahdati, Sahar; Aykul, Can; Lehmann, Jens

5* Knowledge Graph Embeddings with Projective Transformations Konferenzbeitrag

In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, S. 9064–9072, AAAI Press, 2021.

Abstract | BibTeX | Schlagwörter: Selected Publication | Links:

Unveiling Scholarly Communities over Knowledge Graphs

Vahdati, Sahar; Palma, Guillermo; Nath, Rahul Jyoti; Lange, Christoph; Auer, Sören; Vidal, Maria-Esther

Unveiling Scholarly Communities over Knowledge Graphs Konferenzbeitrag

In: Méndez, Eva; Crestani, Fabio; Ribeiro, Cristina; David, Gabriel; Lopes, João Correia (Hrsg.): Digital Libraries for Open Knowledge, 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Porto, Portugal, September 10-13, 2018, Proceedings, S. 103–115, Springer, 2018.

Abstract | BibTeX | Schlagwörter: Selected Publication | Links:

OpenResearch: Collaborative Management of Scholarly Communication  Metadata

Vahdati, Sahar; Arndt, Natanael; Auer, Sören; Lange, Christoph

OpenResearch: Collaborative Management of Scholarly Communication Metadata Konferenzbeitrag

In: Blomqvist, Eva; Ciancarini, Paolo; Poggi, Francesco; Vitali, Fabio (Hrsg.): Knowledge Engineering and Knowledge Management - 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings, S. 778–793, 2016.

Abstract | BibTeX | Schlagwörter: Selected Publication | Links:

SEE ALSO

Ali, Semab

Design and Development of Murphy System: Generating Meaningful Negative Samples for KGEs Abschlussarbeit

University of Bonn, Germany, 2022.

BibTeX | Schlagwörter: FinishedThesis | Links:

Vlad, Adriano; Vahdati, Sahar; Nayyeri, Mojtaba; Bellomarini, Luigi; Sallinger, Emanuel

Towards Hybrid Logic-based and Embedding-based Reasoning on Financial Knowledge Graphs Konferenzbeitrag

In: Ramanath, Maya; Palpanas, Themis (Hrsg.): Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, Edinburgh, UK, March 29, 2022, CEUR-WS.org, 2022.

BibTeX | Schlagwörter: | Links:

Bellomarini, Luigi; Fayzrakhmanov, Ruslan R.; Gottlob, Georg; Kravchenko, Andrey; Laurenza, Eleonora; Nenov, Yavor; Reissfelder, Stéphane; Sallinger, Emanuel; Sherkhonov, Evgeny; Vahdati, Sahar; Wu, Lianlong

Data science with Vadalog: Knowledge Graphs with machine learning and reasoning in practice Artikel

In: Future Gener. Comput. Syst., Bd. 129, S. 407–422, 2022.

BibTeX | Schlagwörter: | Links:

Kumar, Abishek

Going Beyond the Paradigm of Knowledge Graph Embedding Models Abschlussarbeit

University of Bonn, 2022.

BibTeX | Schlagwörter: FinishedThesis | Links:

Fazeli-Varzaneh, Mohsen; Ghorbi, Ali; Ausloos, Marcel; Sallinger, Emanuel; Vahdati, Sahar

Sleeping Beauties of Coronavirus Research Artikel

In: IEEE Access, Bd. 9, S. 21192–21205, 2021.

BibTeX | Schlagwörter: | Links:

Nayyeri, Mojtaba; Cil, Gökce Müge; Vahdati, Sahar; Osborne, Francesco; Kravchenko, Andrey; Angioni, Simone; Salatino, Angelo A.; Recupero, Diego Reforgiato; Motta, Enrico; Lehmann, Jens

Link Prediction of Weighted Triples for Knowledge Graph Completion Within the Scholarly Domain Artikel

In: IEEE Access, Bd. 9, S. 116002–116014, 2021.

BibTeX | Schlagwörter: | Links:

Open THESIS

Finished THESIS

Ali, Semab

Design and Development of Murphy System: Generating Meaningful Negative Samples for KGEs Abschlussarbeit

University of Bonn, Germany, 2022.

BibTeX | Schlagwörter: FinishedThesis | Links:

Kumar, Abishek

Going Beyond the Paradigm of Knowledge Graph Embedding Models Abschlussarbeit

University of Bonn, 2022.

BibTeX | Schlagwörter: FinishedThesis | Links:

Aykul, Can

Unveiling the Effect of using Moebius Transformations on Knowledge Graph Embeddings Abschlussarbeit

University of Bonn, Germany , 2020.

BibTeX | Schlagwörter: FinishedThesis | Links:

VACANCIES

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