Über Sahar Vahdati

Group Lead at InfAI - Institute for Applied Informatics (Nature-Inspired Machine Intelligence Research Group)

Link Prediction using Numerical Weights for Knowledge Graph Completion within the Scholarly Domain

2021-01-31T12:14:11+01:00

Abstract Knowledge graphs (KGs) are widely used for modeling scholarly communication, informing scientometric analysis, and supporting a variety of intelligent services to explore the literature and predict research dynamics. However, they often suffer from [...]

Link Prediction using Numerical Weights for Knowledge Graph Completion within the Scholarly Domain2021-01-31T12:14:11+01:00

Image Processing with Generative Adversarial Networks Description

2020-12-13T22:14:35+01:00

Multimodal knowledge graphs (MMKG) are getting a huge attraction from the AI community. Image is a modal which has a lot of hidden knowledge inside and is an old topic from the computer vision [...]

Image Processing with Generative Adversarial Networks Description2020-12-13T22:14:35+01:00

Geometric Neural Networks

2020-12-13T22:43:55+01:00

Neural Networks have shown promising performance in various tasks including classification, regression and clustering. Performance of NNs depends on the underlying geometry they designed on. However, most NNs are designed while they are unaware [...]

Geometric Neural Networks2020-12-13T22:43:55+01:00

Applied Mathematics in Artificial Intelligence

2020-12-13T22:44:24+01:00

We open an opportunity with our support for those computer scientists in the master level who have been a big fan of mathematics, however could not find a strong bridging of this knowledge and [...]

Applied Mathematics in Artificial Intelligence2020-12-13T22:44:24+01:00

Dr. Sahar Vahdati

2021-01-28T18:31:04+01:00

Dr. Sahar Vahdati Group Leader Nature-Inspired Machine Learning (NIMI) Biography Nature, and all that it encompasses, has influenced computer science, in particular Artificial Intelligence, from its inception. Many effective [...]

Dr. Sahar Vahdati2021-01-28T18:31:04+01:00

Workshop of Knowledge Representation & Representation Learning

2021-01-03T20:29:19+01:00

The workshop ‘Knowledge Representation & Representation Learning (KR4L)’ will be held in conjunction with the 24th European Conference on Artificial Intelligence (ECAI 2020). There currently is a perceived disconnect between the areas of Representation [...]

Workshop of Knowledge Representation & Representation Learning2021-01-03T20:29:19+01:00

5* Knowledge Graph Embeddings with Projective Transformations

2021-01-31T12:17:54+01:00

Abstract Performing link prediction using knowledge graph embedding (KGE) models is a popular approach for knowledge graph completion. Such link predictions are performed by measuring the likelihood of links in the graph via a [...]

5* Knowledge Graph Embeddings with Projective Transformations2021-01-31T12:17:54+01:00

Reasoning in Knowledge Graphs: An Embeddings Spotlight

2021-01-03T13:12:17+01:00

Abstract In this chapter we introduce the aspect of reasoning in Knowledge Graphs. As in Chap. 2, we will give a broad overview focusing on the multitude of reasoning techniques: spanning logic-based reasoning, embedding-based [...]

Reasoning in Knowledge Graphs: An Embeddings Spotlight2021-01-03T13:12:17+01:00

Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation)

2021-01-19T15:16:58+01:00

Abstract The increasing interest in analysing, describing, and improving the research process requires the development of new forms of scholarly data publication and analysis that integrates lessons and approaches from the field of Semantic [...]

Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation)2021-01-19T15:16:58+01:00
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