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19 Jun 2024: Each histogramrepresents the ranking across the test set assigned by the designated feature importance method. ... These results suggest that ourattack is successful in generalising across unseen test points.

19 Nov 2023: Show and comment on the fit and the hypers, and the predictions forthe test data.

19 Nov 2023: Show and comment on the fit and the hypers, and the predictions forthe test data.

19 Jun 2024: Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10 with 4 workers (on the left) and 16 workers (on the right). ... Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10.

19 Jun 2024: Table 2 shows p-values for paired t-tests examining outperformance of each model compared to the baseline HMMv approach. ... Figure 2 shows the TOM test accuracies for all the models trained using Hamming distance as before.

19 Nov 2023: c) For the Bayesian model, what is the log probability for the test document with ID 2001? ... Explainwhether, when computing the log probability of a test document, you would use the multinomial withor without the “combinatorial factor”.

19 Jun 2024: We evaluate the test set of fours, sevens, and nines with our BNN. ... This group was able to reach an accuracyof 88% on unseen test points.

19 Nov 2023: generalize from observations in the training set to new test cases(interpolation and extrapolation). • ... make predictions on test cases• interpret the trained model, what insights is the model providing?• evaluate the accuracy of model. •

19 Jun 2024: To test the nature of these outputs we introduce a novel saliencymap approach, termed MIG-SG. ... To test this, we evaluated the sensitivity of DIP to changes innetwork architecture.

19 Nov 2023: Constraint-Based Learning: Use statistical tests of marginal and conditionalindependence. Find the set of DAGs whose d-separation relations match theresults of conditional independence tests.