Higher order kernel mean embeddings to capture filtrations of stochastic processes
Stochastic processes are random variables with values in some space of paths. However, reducing a stochastic process to a path-valued random variable ignores its filtration, i.e. the flow of information carried by the process through time. By conditioning the process on its filtration, we introduce...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Curran Associates
2022
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