While 3DGaussian Splatting has recently become popular for neural rendering, current methods rely on carefully engineered cloning and splitting strategies for placing Gaussians, which can lead to poor-quality renderings, and reliance on a goodinitialization.

However, there still exist many properties of contrastive learning that are not guaranteed.

Wearable robotics are moving from research labs into everyday life as powered shoes and exoskeletons become consumer products designed to support natural movement.

An elephant foot bone found by archaeologists digging in southern Spain may be evidence that a troop of war elephants stomped through ancient Europe. It would be the first concrete proof of the legendary Carthaginian General Hannibal's troop of battle elephants, according to academics. Drawings of Hannibal's war against the Romans had long suggested that the beasts were used in fighting, but no hard evidence backed up the theories. Now the creatures' skeletal remains appear to have been found in an Iron Age dig near Cordoba. Beyond ivory, the discovery of elephant remains in European archaeological contexts is exceptionally rare, says the team of scientists in a paper published in Journal of Archaeological Science: Reports.

A.1 PCNtraining We basically follow the same PCN training method by Wu et al.[1] but replace the AlphaZero algorithm with the Gumbel AlphaZero algorithm [2], where the simulation count is set to 322 in self-play and starts by sampling 16 actions. The architecture of the PCN contains three residual blocks with 256 hidden channels. Atotal of400,000 self-play games are generated for the whole training. During optimization, the learning rate is fixed at 0.02, and the batch size is set to 1,024. A.3 Workerdesign The worker is itself a Killall-Go solver. Thus,tofullyutilize GPU resources, we implement batch GPU inferencing to accelerate PCN evaluations for workers.