We sometimes need our reinforcement learning agents to be robust to different physics than they are trained with, such as when attempting a sim2real policy transfer. Using domain randomization, we ...

Previous Mendelian randomization (MR) studies on obesity and risk of breast cancer adopted a small number of instrumental variables and focused mainly on the crude total effect. We aim to investigate ...

The rise of deep learning has caused a paradigm shift in robotics research, favoring methods that require large amounts of data. Unfortunately, it is prohibitively expensive to generate such data sets ...

IsaacGymEnvs supports "on the fly" domain randomization, allowing dynamics to be changed when resetting the environment, but without requiring reloading of assets. This allows us to efficiently apply ...

Because individual-level GWAS data were not available, we used the recently rapidly expanding application tool of two-sample MR analyses to evaluate the causal effect of body fat mass and distribution ...

Introduction: Previous studies have suggested that increased body fat is associated with stroke risk. Advances in imaging-based fat distribution measurements have uncovered distinct biological ...

In an effort to investigate the effect of positional distribution on oxidative stability of menhaden and seal blubber oils, Novozyme 435 was used as a random biocatalyst. Positional distribution of ...