8 citations · 15 across the 5 of their papers we have counts for
5 papers
Kernelized Cumulants: Beyond Kernel Mean Embeddings
Patric Bonnier, Harald Oberhauser, Zoltán Szabó
In , it is well-known that cumulants provide an alternative to moments that can achieve the same goals with numerous benefits such as lower variance estimators. In thi…
Proper Scoring Rules, Gradients, Divergences, and Entropies for Paths and Time Series
Patric Bonnier, Harald Oberhauser
Many forecasts consist not of point predictions but concern the evolution of quantities. For example, a central bank might predict the interest rates during the next quarter, an ep…
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
Csaba Toth, Patric Bonnier, Harald Oberhauser
Sequential data such as time series, video, or text can be challenging to analyse as the ordered structure gives rise to complex dependencies. At the heart of this is non-commutati…
Adapted Topologies and Higher Rank Signatures
Patric Bonnier, Chong Liu, Harald Oberhauser
The topology of weak convergence does not account for the growth of information over time that is captured in the filtration of an adapted stochastic process. For example, two adap…
Signature Cumulants, Ordered Partitions, and Independence of Stochastic Processes
Patric Bonnier, Harald Oberhauser
The sequence of so-called signature moments describes the laws of many stochastic processes in analogy with how the sequence of moments describes the laws of vector-valued random v…