A Proofs

Evaluation The evaluation methods we used are summarized in Algorithm 2 and Algorithm 3. We summarize the hyperparameters used for our evaluations in Table 3. T able 3: Hyperparameters used for evaluations. B.2 Implementation details for BPC-rKL To obtain a Bayesian pseudocoreset with reverse KL divergence by Algorithm 1 in [19], we need to Require: Differentiable augmentation function A (Optional). Figure 1b, we show the accuracy with varying variances. 's are presented as colors. Table 5 shows additional results for the CIFAR10 dataset when the pseudocoreset size is larger. Even in these cases, BPC-W and BPC-fKL effectively generate Bayesian pseudocoresets.