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  2. Compression without Quantization Gergely Flamich Department of…

    https://www.mlmi.eng.cam.ac.uk/files/compression_without_quantization_flamich_reduced.pdf
    18 Nov 2019: For our results to be comparable to these methods, we have alsodecided to test our method on the Kodak dataset.
  3. PROBABILISTIC PROGRAMMING IN JULIA:NEW INFERENCE ALGORITHMS KAI XU…

    https://www.mlmi.eng.cam.ac.uk/files/xu_kai_industry_day_poster.pdf
    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.
  4. Probabilistic Programming in JuliaNew Inference Algorithms Kai Xu…

    https://www.mlmi.eng.cam.ac.uk/files/kai_xu_8224821_assignsubmission_file_xu_kai_dissertation.pdf
    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.
  5. Uncertainty in Bayesian Neural Networks

    https://www.mlmi.eng.cam.ac.uk/files/uncertainty_in_bayesian_neural_networks_v2.pdf
    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. Overcoming Catastrophic Forgetting in Neural Machine Translation

    https://www.mlmi.eng.cam.ac.uk/files/kell_thesis.pdf
    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
  7. Pathologies of Deep Sparse Gaussian Process Regression

    https://www.mlmi.eng.cam.ac.uk/files/diaz_thesis.pdf
    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:.
  8. MLMI4_Team1_Poster2

    https://www.mlmi.eng.cam.ac.uk/files/variational_continual_learning_in_deep_discriminative_models.pdf
    14 Nov 2019: for task in previous tasks# incorporate coreset)5W(#) = proj()5 # , T5)# make predictionget_score(test_x, test_y, )5W(#)).
  9. Training Restricted BoltzmannMachines Using High-Temperature…

    https://www.mlmi.eng.cam.ac.uk/files/pawel_budzianowski_8224891_assignsubmission_file_budzianowski_dissertation.pdf
    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
  10. Well-Calibrated Bayesian NeuralNetworks On the empirical assessment…

    https://www.mlmi.eng.cam.ac.uk/files/jheek_thesis.pdf
    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.
  11. 3D Human Motion Synthesis with Recurrent Gaussian Processes

    https://www.mlmi.eng.cam.ac.uk/files/3d_human_motion_synthesis_with_recurrent_gaussian_processes_yeziwei_wang.pdf
    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.

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