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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Multi-Source Neural Variational Inference

February 1, 2023

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Authors

Richard Kurle

Technical University of Munich


Stephan Günnemann

Technical University of Munich


Patrick van der Smagt

Volkswagen Group


DOI:

10.1609/aaai.v33i01.33014114


Abstract:

Learning from multiple sources of information is an important problem in machine-learning research. The key challenges are learning representations and formulating inference methods that take into account the complementarity and redundancy of various information sources. In this paper we formulate a variational autoencoder based multi-source learning framework in which each encoder is conditioned on a different information source. This allows us to relate the sources via the shared latent variables by computing divergence measures between individual source’s posterior approximations. We explore a variety of options to learn these encoders and to integrate the beliefs they compute into a consistent posterior approximation. We visualise learned beliefs on a toy dataset and evaluate our methods for learning shared representations and structured output prediction, showing trade-offs of learning separate encoders for each information source. Furthermore, we demonstrate how conflict detection and redundancy can increase robustness of inference in a multi-source setting.

Topics: AAAI

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HOW TO CITE:

Richard Kurle||Stephan Günnemann||Patrick van der Smagt Multi-Source Neural Variational Inference Proceedings of the AAAI Conference on Artificial Intelligence (2019) 4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt Multi-Source Neural Variational Inference AAAI 2019, 4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt (2019). Multi-Source Neural Variational Inference. Proceedings of the AAAI Conference on Artificial Intelligence, 4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. Multi-Source Neural Variational Inference. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. 2019. Multi-Source Neural Variational Inference. "Proceedings of the AAAI Conference on Artificial Intelligence". 4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. (2019) "Multi-Source Neural Variational Inference", Proceedings of the AAAI Conference on Artificial Intelligence, p.4114-4121

Richard Kurle||Stephan Günnemann||Patrick van der Smagt, "Multi-Source Neural Variational Inference", AAAI, p.4114-4121, 2019.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. "Multi-Source Neural Variational Inference". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. "Multi-Source Neural Variational Inference". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 4114-4121.

Richard Kurle||Stephan Günnemann||Patrick van der Smagt. Multi-Source Neural Variational Inference. AAAI[Internet]. 2019[cited 2023]; 4114-4121.


ISSN: 2374-3468


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