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31 - 40 of 164 search results for Economics test |u:www.mlmi.eng.cam.ac.uk where 13 match all words and 151 match some words.

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  2. Constrained Bayesian Optimization for Automatic Chemical Design

    https://www.mlmi.eng.cam.ac.uk/files/griffiths_dissertation.pdf
    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.

  3. Waveform Level Synthesis

    https://www.mlmi.eng.cam.ac.uk/files/dou_thesis.pdf
    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.

  4. Conditional Neural ProcessesWeisz S., Buonomo, A, Yuang, L,…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/conditional_neural_processes_1_2022.pdf
    17 May 2022: Extension: ConvCNPs. Maximum Likelihood Training. Desirable Properties1. Data-efficient (using meta-learning)2. Fast predictions at test time: đť’Ş đť‘› đť‘š for predicting.

  5. Designing Neural Network Hardware Accelerators Using Deep Gaussian…

    https://www.mlmi.eng.cam.ac.uk/files/havasi_dissertation.pdf
    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. Neural Network Compression

    https://www.mlmi.eng.cam.ac.uk/files/okz21_thesisfinal.pdf
    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.

  7. Interpretable Machine Learning Tyler Martin Supervisor: Dr. Adrian…

    https://www.mlmi.eng.cam.ac.uk/files/tam_final_reduced.pdf
    18 Nov 2019: This project explores many. aspects of the algorithm, tests its limits, and proposes best practices for practitioners.

  8. Augmenting Natural Language Generation with external memory modules…

    https://www.mlmi.eng.cam.ac.uk/files/minglong_sun_mphil_thesis.pdf
    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.

  9. Variational Inference in Deep Directed Latent Variable ModelsRiashat…

    https://www.mlmi.eng.cam.ac.uk/files/variational_inference_in_deep_directed_latent_variable_models.pdf
    30 Oct 2019: Experimental Results. Figure below shows test set performance dor different dimensionality of latent space.

  10. Strengths/Weaknesses Synthetic 1-D Distributions Towards a Neural…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/towards_a_neural_statistician_2022.pdf
    17 May 2022: 3.2. 5.4. Statistics Network. StatisticsNetwork. 2.3. Trained on OMNIGLOT, test imagex is classified to a seen dataset:.

  11. PowerPoint Presentation

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/first-order_approximations_for_efficient_meta-learning_2022.pdf
    17 May 2022: zero. Lastly, overfitting on the test task can be seen after about 20 ADAM inner-loop iterations when trained for many meta iterations. ... Figure 5: Example 5-way classifier: 1-shot images (top row) and test images (bottom row).

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