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30 Oct 2019: Some hand-written models were used to test these two com-ponents. In addition, the student is also contribut-ing to the documentation work.

18 Nov 2019: For our results to be comparable to these methods, we have alsodecided to test our method on the Kodak dataset.

30 Oct 2019: With model parameters learnt, models can be used to test new data Dnew bycalculating. ... testing the model on the testing set, or 2) test whethersome incoming data is from the same data set or not.

14 Nov 2019: Table: MNIST test results for methods under consideration. We approximate Eq(w)[p(y′|x′, w)] with 100 MC samples. ... Figure: MAP results in overconfidence on MNIST-test.Approximate inference methods are underconfident for high p.

6 Nov 2019: English Test CorpusTokens 108707 98998 207187Types 18545 20194 33331. Sentences 5027 4028 8857. ... Spanish Test CorpusTokens 124866 109067 231744Types 21457 21985 37530. Sentences 5027 4028 8857Table 3.1 Statistics of training and tests used in NMT

30 Oct 2019: 33. 5.3 Out-sample test scores for with Ntr = 500, M = 25. ... aclosed-form expression for the predictive distribution at a new test point x:.

14 Nov 2019: for task in previous tasks# incorporate coreset)5W(#) = proj()5 # , T5)# make predictionget_score(test_x, test_y, )5W(#)).

30 Oct 2019: Training Restricted BoltzmannMachines Using High-Temperature. Expansions. Paweł Budzianowski. Department of EngineeringUniversity of Cambridge. M.Phil in Machine Learning, Speechand Language Technology. This dissertation is submitted for the degree

6 Nov 2019: Otherwise it would be trivial to construct a failing calibration test forany model. ... Calibration tests could help alleviate thisissue which is otherwise inevitable for popular benchmarks.

6 Nov 2019: For prediction, the initial 20 frames of the test sequence are fed to the trained model for motion generation. ... 4 Different motions will be explored to test howwell the model generalises.

6 Nov 2019: The objective is topredict the value f(x) for a test data point x. ... The predictive distribution gives the dataspace representation for a test latent space point.

30 Oct 2019: 30. 5.3 Pose data: average ELBO over the test set (175,638 samples). ... 5.9 Pose data: average ELBO over the test set (175,638 samples).

6 Nov 2019: The smaller network can then be used for fast approximations to theBayesian teacher network at test time. ... This results in high storage savings, however at test time,the full weight matrix needs to be restored again, resulting in no memory savings.

6 Nov 2019: 437.6 Test gap (train evidence - test evidence) at peak test performance of SP-VAE vs VAE. ... Notice the green curve. 487.10 Test evidence on SVHN against fraction of SPN parameters in sum nodes.

30 Oct 2019: They apply their method to few-shot classi-fication as an example test bed. ... Additionally to test accuracies, we also report the. 3.2 Implementation and experimental setup 27.

6 Nov 2019: Figure 1d shows the average cross entropy for theheld-out test data as a function of the differentdatasets and stochastic variable dimension.

6 Nov 2019: Success rate of adversarial examples. • Model accuracy vs. % adversarial examples in test set. •

6 Nov 2019: 374.5 Fidelity test for fake feature maps generated by unconditional GANs: ’aa’. ... aa’ ). 354.3 Classification accuracies for CGANs’ samples and TIMIT test set (phone:.

30 Oct 2019: 446.5 Comparison of development and test PPL values of the TF-RNNLM. ... TF-RNNLM-GRU). 486.8 Development and Test PPL for each of the dierent systems.

30 Oct 2019: The standard error is given for 5 separatetrain/test set splits of 90/10. ... TheResults of 5 Separate Train/Test Set Splits of 90/10 are Provided.

30 Oct 2019: 123.2 test NLL in bits for 2-tier and 3-tier models. 20. ... Table 3.2 test NLL in bits for 2-tier and 3-tier models.

30 Oct 2019: 424.2 Training and test log-likelihoods during training. 434.3 Runtime of the training process for the two implementations. ... The test log-likelihood of the GPmodel was 1.200.06 as opposed to 0.610.04 of DGPs and 0.480.05 of JointDGPs at 300 training

6 Nov 2019: Tests show that throughthis technique, the drop in accuracy for MobileNet network for ImageNet challenge reducesby a mere 1-2% [22]. ... The dataset consists of the 60,000 training and 10,000 test 28 28 pixel examples of the 10 digits.

6 Nov 2019: 385.2.2 Main results. 385.2.3 Models’ performances on unseen test data. 405.2.4 Discussions. ... jointly on SF Multi-Domain. 405.8 Numbers of DA in unique and non-overlap test sets across the domains in.

18 Nov 2019: This project explores many. aspects of the algorithm, tests its limits, and proposes best practices for practitioners.

30 Oct 2019: Experimental Results. Figure below shows test set performance dor different dimensionality of latent space.

30 Oct 2019: A similar pipeline is followed for new test data. The second (M2) approach proposed extending the VAE model to include labels, asdepicted in Figure 3.1.