Multimodal probabilistic reasoning for prediction and coordination problems in machine learning
<p>In this thesis we consider the role of multimodality in decision making and coordination problems in machine learning. We propose the use of a series of multimodal probabilistic methods, using extensions of (finite) mixture models to tackle challenges in time series forecasting, efficient u...
Huvudupphovsman: | Zand, J |
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Övriga upphovsmän: | Roberts, S |
Materialtyp: | Lärdomsprov |
Språk: | English |
Publicerad: |
2021
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Ämnen: |
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