Search Results for author:
Found 8 papers, 2 papers with code
player2vec: A Language Modeling Approach to Understand Player Behavior in Games
Methods for learning latent user representations from historical behavior logs have gained traction for recommendation tasks in e-commerce, content streaming, and other settings.
Rooms with Text: A Dataset for Overlaying Text Detection
In this paper, we introduce a new dataset of room interior pictures with overlaying and scene text, totalling to 4836 annotated images in 25 product categories.
TensorFlow RiemOpt: a library for optimization on Riemannian manifolds
The adoption of neural networks and deep learning in non-Euclidean domains has been hindered until recently by the lack of scalable and efficient learning frameworks.
ZCal: Machine learning methods for calibrating radio interferometric data
The average prediction error obtained during the testing of our models on testing data is $ \approx 0. 01 < rmse < 0. 09$ for gain amplitude per antenna, and $0. 2 rad < rmse <0. 5 rad$ for gain phase.
Temporal assortment of cooperators in the spatial prisoner's dilemma
We study a spatial, one-shot prisoner's dilemma (PD) model in which selection operates on both an organism's behavioral strategy (cooperate or defect) and its choice of when to implement that strategy across a set of discrete time slots.
Comparison of classical and Bayesian imaging in radio interferometry
CLEAN, the commonly employed imaging algorithm in radio interferometry, suffers from a number of shortcomings: in its basic version it does not have the concept of diffuse flux, and the common practice of convolving the CLEAN components with the CLEAN beam erases the potential for super-resolution; it does not output uncertainty information; it produces images with unphysical negative flux regions; and its results are highly dependent on the so-called weighting scheme as well as on any human choice of CLEAN masks to guiding the imaging.
Instrumentation and Methods for Astrophysics Applications
Radio interferometric gain calibration as a complex optimization problem
We apply these developments to the problem of radio interferometric gain calibration, and show how the general complex Jacobian formalism, when combined with conventional optimization approaches, yields a whole new family of calibration algorithms, including those for the polarized and direction-dependent gain regime.
Instrumentation and Methods for Astrophysics
Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations
Chi-squared values computed from the model and observed visibilities are used as likelihood values to drive the Bayesian sampling process and select the best sky model.
