Automated seizure detection is of great importance to epilepsy diagnosis and treatment.

Many animals learn cognitive maps of their environment - a simultaneous representation of context, experience, and position.

This paper examines learning the optimal filtering policy, known as the Kalman gain, for a linear system with unknown noise covariance matrices using noisy output data. The learning problem is formulated as a stochastic policy optimization problem, aiming to minimize the output prediction error. This formulation provides a direct bridge between data-driven optimal control and, its dual, optimal filtering.

Beyond estimating parameters of interest from data, one of the key goals of statistical inference is to properly quantify uncertainty in these estimates.

These estimates are subsequently utilized to aggregate information from reference frames into the target frame. Subsequently, hierarchical neural point clouds are constructed based on the aggregated information. This hierarchical point cloud set is then employed to synthesize views of the target frame.

However error control for inverse graphics is difficult, and inverse graphics methods can represent only the effects of the chosen intrinsics.

Leveraging this flexibility, we implement 47 novel MCBO algorithms and benchmark them against seven existing MCBO solvers and five standard black-box optimization algorithms on ten tasks, conducting over 4000 experiments.

Samsung Galaxy Unpacked 2026 is Feb. 25 Valve's Steam Machine: Everything we know EU launches second investigation into Grok's nonconsensual image generation Grok has been accused of creating sexual images of children, alongside other violations. X is facing yet another investigation into Grok's reported creation of nonconsensual sexual images on the platform. Ireland's Data Protection Commission (DPC) has announced an inquiry into X regarding the harmful, intimate images and processing of EU and EEA individuals' personal data -- including children. In an 11-day period, X generated about three million sexualized images, an estimated 23,000 of which were of children. British nonprofit, the Center for Countering Digital Hate (CCDH) announced the results of its December 29 to January 9 review last month.