The capability of determining the right physical action to achieve a given task is essential for AI that interacts with the physical world. The great difficulty in developing this capability has two main causes: (1) the world is continuous and therefore the action space is infinite, (2) due to noisy perception, we do not know the exact physical properties of our environment and therefore cannot...

We analyse the stochastic background of gravitational radiation emitted by a cosmological population of core-collapse supernovae. The supernova rate as a function of redshift is deduced from an observation-based determination of the star formation rate density evolution. We then restrict our analysis to the range of progenitor masses leading to black hole collapse. In this case, the main featur...

I review the temporal/spectral data of accreting black hole sources paying most attention to the properties of the temporal variability such as photon energy dependent autoand cross-correlation functions, average shot profiles and hardness ratios, and the Fourier frequency dependent time/phase lags. These statistics characterize spectral changes at short time scales that are otherwise impossibl...

To fill holes in photographs of structured, man made environments, we propose a technique which automatically adjusts and clones large image patches that have similar structure. These source patches can come from elsewhere in the same image, or from other images shot from different perspectives. Two significant developments of this work are the ability to automatically detect and adjust source ...

We study the gravitational wave emission from the first stars which are assumed to be Very Massive Objects (VMOs). We take into account various feedback (both radiative and stellar) effects regulating the collapse of objects in the early universe and thus derive the VMO initial mass function and formation rate. If the final fate of VMOs is to collapse, leaving very massive black hole remnants, ...