SEMANTiCS 2024

By |2024-01-05T17:34:51+01:00September 25th, 2023|

At SEMANTiCS researchers, industry experts and business leaders can develop a thorough understanding of trends and application scenarios in the fields of Machine Learning, Data Science, Linked Data and Natural Language Processing. Important Dates Call for Research & Innovation Papers Abstract Submission Deadline: April 22 , 2024 (11:59 pm, Hawaii time) Paper Submission Deadline: April 29, [...]

SEMANTiCS 2023

By |2024-01-05T17:36:02+01:00September 20th, 2023|

THIS EVENT IS CO-ORGANIZED BY SEMANTiCS & LANGUAGE INTELLIGENCE 2023 At SEMANTiCS researchers, industry experts and business leaders can develop a thorough understanding of trends and application scenarios in the fields of Machine Learning, Data Science, Linked Data and Natural Language Processing. LANGUAGE INTELLIGENCE 2023 is showcasing the latest developments in Multilingual Artificial Intelligence: speech interaction, deep meaning [...]

Algebraic Representation Learning

By |2022-07-01T00:37:23+02:00July 1st, 2022|

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 interest in AI so far. The idea is to connect known mathematical theories in Today’s AI. For example the use [...]

Smart Analytics on Environmental, Medical or Scholarly Graphs using Knowledge Graph Embedding

By |2022-07-01T00:29:54+02:00July 1st, 2022|

There are a huge number of knowledge graphs available for AI-related applications such as smart analysis, link prediction, and recommendation. We focus on three major domains of Environmental, Medical or Scholarly domains and their available datasets. We plan to use embedding models in order to provide smart analytics and link prediction services on them. [...]

Geometric Neural Networks

By |2022-07-01T00:00:59+02:00July 1st, 2022|

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 of the data geometry. We aim at tackling this problem and developing new NNs based on recent findings in geometry [...]

Workshop of Knowledge Representation & Representation Learning

By |2024-01-05T17:36:13+01:00June 20th, 2020|

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 Learning (RL) and Knowledge Representation and Reasoning (KRR). Most of the research is currently concentrated on one area or the [...]

Go to Top