A Bayesian pseudocoreset is a compact synthetic dataset summarizing essential information of a large-scale dataset and thus can be used as a proxy dataset for scalable Bayesian inference. Typically, a Bayesian pseudocoreset is constructed by minimizing a divergence measure between the posterior conditioning on the pseudocoreset and the posterior conditioning on the full dataset. However, evaluating the divergence can be challenging, particularly for the models like deep neural networks having high-dimensional parameters.

Diffusion-based generative models, as first introduced by Sohl-Dickstein et al. (2015), have shown

China's annual gala on Lunar New Year's Eve has showcased Beijing's giant leap in technology as humanoid robots took centre stage to perform a joint martial arts routine featuring several firsts. China's Spring Festival Gala, which aired on Monday on state broadcaster CGTN, has gone viral, drawing nearly half a million views on YouTube. The performance marked a stark contrast with last year's show, when robots twirled handkerchiefs and performed simple movements. The first robots to appear were Noetix's Bumi models, who performed a comedy sketch. Unitree's robots later exhibited martial arts alongside child artists, including backflips and trampoline jumps, followed by Magiclab's humanoids in a musical segment.

Both algorithms yield state-of-the-art performance guarantees.

Currently, two mainstream GNN-based methods have been developed for constructing force fields: group theory-based methods and direction-based methods.

Literal Interpretation: One of the limitations is the model's tendency to interpret questions