7 citations · 7 across the 5 of their papers we have counts for
5 papers
Explicit Density Approximation for Neural Implicit Samplers Using a Bernstein-Based Convex Divergence
José Manuel de Frutos, Manuel A. Vázquez, Pablo M. Olmos +1
Rank-based statistical metrics, such as the invariant statistical loss (ISL), have recently emerged as robust and practically effective tools for training implicit generative model…
Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss
José Manuel de Frutos, Manuel A. Vázquez, Pablo Olmos +1
Traditional implicit generative models are capable of learning highly complex data distributions. However, their training involves distinguishing real data from synthetically gener…
Training Implicit Generative Models via an Invariant Statistical Loss
José Manuel de Frutos, Pablo M. Olmos, Manuel A. Vázquez +1
Implicit generative models have the capability to learn arbitrary complex data distributions. On the downside, training requires telling apart real data from artificially-generated…
Importance sampling with transformed weights
Manuel A. Vázquez, Joaquín Míguez
The importance sampling (IS) method lies at the core of many Monte Carlo-based techniques. IS allows the approximation of a target probability distribution by drawing samples from…
The wideband backend at the MDSCC in Robledo. A new facility for radio astronomy at Q- and K- bands
J. R. Rizzo, A. Pedreira, M. Gutiérrez +11
The antennas of NASA's Madrid Deep Space Communications Complex (MDSCC) in Robledo de Chavela are available as single-dish radio astronomical facilities during a significant percen…