18 citations · 37 across the 6 of their papers we have counts for
6 papers
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift
Luca Masserano, Syama Sundar Rangapuram, Shubham Kapoor +3
The world is not static: This causes real-world time series to change over time through external, and potentially disruptive, events such as macroeconomic cycles or the COVID-19 pa…
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
Jeha Paul, Bohlke-Schneider Michael, Mercado Pedro +5
Realistic synthetic time series data of sufficient length enables practical applications in time series modeling tasks, such as forecasting, but remains a challenge. In this paper…
Bayesian Quantile Matching Estimation
Rajbir-Singh Nirwan, Nils Bertschinger
Due to increased awareness of data protection and corresponding laws many data, especially involving sensitive personal information, are not publicly accessible. Accordingly, many…
Rotation Invariant Householder Parameterization for Bayesian PCA
Rajbir S. Nirwan, Nils Bertschinger
We consider probabilistic PCA and related factor models from a Bayesian perspective. These models are in general not identifiable as the likelihood has a rotational symmetry. This…
Applications of Gaussian Process Latent Variable Models in Finance
Rajbir-Singh Nirwan, Nils Bertschinger
Estimating covariances between financial assets plays an important role in risk management. In practice, when the sample size is small compared to the number of variables, the empi…
Emergent Chiral Spin State in the Mott Phase of a Bosonic Kane-Mele-Hubbard Model
Kirill Plekhanov, Ivana Vasić, Alexandru Petrescu +4
Recently, the frustrated XY model for spins-1/2 on the honeycomb lattice has attracted a lot of attention in relation with the possibility to realize a chiral spin liquid state. Th…