7 citations · 19 across the 6 of their papers we have counts for
6 papers
Hellinger loss function for Generative Adversarial Networks
Giovanni Saraceno, Anand N. Vidyashankar, Claudio Agostinelli
We propose Hellinger-type loss functions for training Generative Adversarial Networks (GANs), motivated by the boundedness, symmetry, and robustness properties of the Hellinger dis…
Weighted likelihood methods for robust fitting of wrapped models for -torus data
Claudio Agostinelli, Luca Greco, Giovanni Saraceno
We consider robust estimation of wrapped models to multivariate circular data that are points on the surface of a -torus based on the weighted likelihood methodology.Robust mode…
A Robust Seemingly Unrelated Regressions For Row-Wise And Cell-Wise Contamination
Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli
The Seemingly Unrelated Regressions (SUR) model is a wide used estimation procedure in econometrics, insurance and finance, where very often, the regression model contains more tha…
Robust Estimation for Multivariate Wrapped Models
Giovanni Saraceno, Claudio Agostinelli, Luca Greco
A weighted likelihood technique for robust estimation of a multivariate Wrapped Normal distribution for data points scattered on a p-dimensional torus is proposed. The occurrence o…
Robust Estimation under Linear Mixed Models: The Minimum Density Power Divergence Approach
Giovanni Saraceno, Abhik Ghosh, Ayanendranath Basu +1
Many real-life data sets can be analyzed using Linear Mixed Models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the infe…
Robust Multivariate Estimation Based On Statistical Depth Filters
Giovanni Saraceno, Claudio Agostinelli
In the classical contamination models, such as the gross-error (Huber and Tukey contamination model or Case-wise Contamination), observations are considered as the units to be iden…