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  2. Auto-Encoding Variational BayesPawe l F. P. Budzianowski, Thomas F.…

    https://www.mlmi.eng.cam.ac.uk/files/mlsalt4_budzianowski_nicholson_tebbutt.pdf
    30 Oct 2019: 200. 180. 160. 140. 120. 100. L. MNIST, Defualt AEVB. 0.0 0.2 0.4 0.6 0.8 1.01e8. ... 0.0 0.2 0.4 0.6 0.8 1.01e8. 220. 200. 180. 160. 140.
  3. Auto-Encoding Variational Bayes

    https://www.mlmi.eng.cam.ac.uk/files/auto_encoding_var_bayes_d423c.pdf
    6 Nov 2019: 50. 100. 150. 200. 250. 300. Num. ber. of. dim. ensi. ... Squares of weights of dimensions. 0. 50. 100. 150. 200. 250.
  4. Auto-Encoding Variational Bayes

    https://www.mlmi.eng.cam.ac.uk/files/e520t_auto_encoding_variational_bayes.pdf
    6 Nov 2019: We observe thatincreasing the number of latent variables from 20 to 200 does not lead to overfitting. ... 105 106 107 108150. 140. 130. 120. 110. 100. 90MNIST, Nz = 200.
  5. Structured Priors for Policy Optimisation

    https://www.mlmi.eng.cam.ac.uk/files/structured-priors-policy_wang.pdf
    30 Oct 2019: 0. 50. 100. 150. 200. 250. 300. Reward. Learning Curve for Swimmer.
  6. Uncertainty in Bayesian Neural Networks

    https://www.mlmi.eng.cam.ac.uk/files/uncertainty_in_bayesian_neural_networks_v2.pdf
    14 Nov 2019: We use a single-outputFC network with one hidden layer of 200 ReLU units to predict the regression mean µ(x). ... We use atwo-head network with 200 ReLU units to predict the regression mean µ(x) and log-standard deviation log σ(x).
  7. Fact Checking Fake News

    https://www.mlmi.eng.cam.ac.uk/files/2019_06_17_poster_industry_presentation_bart_melman.pdf
    15 Nov 2019: quick. Fever Challenge. DataCorpus 6 million Wikipedia pagesTraining Set 200 thousand claims.
  8. Sequential Neural Models with Stochastic Layers

    https://www.mlmi.eng.cam.ac.uk/files/d402k_poster_sequential_neural_models_with_stochastic_layers.pdf
    6 Nov 2019: We then used a separated testingset to measure the ELBO of different SRNN archi-tectures, namely for z R(2,10,25,50,100,200) and ford
  9. Curiosity-Driven Reinforcement Learning for Dialogue Management

    https://www.mlmi.eng.cam.ac.uk/files/paulawesselmann_mlsalt.pdf
    6 Nov 2019: 33. 4.5 Actions the policy has learned to use after training for 200, 400, and 600dialogues and corresponding curiosity rewards those actions received.
  10. MergedFile

    https://www.mlmi.eng.cam.ac.uk/files/de_jong_thesis.pdf
    6 Nov 2019: Compressing neural networks. Sjoerd Roelof de JongFitzwilliam College. A dissertation submitted to the University of Cambridgein partial fulfilment of the requirements for the degree of. Master of Philosophy in Machine Learning, Speech, and
  11. Designing Neural Network Hardware Accelerators Using Deep Gaussian…

    https://www.mlmi.eng.cam.ac.uk/files/havasi_dissertation.pdf
    30 Oct 2019: 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 points.
  12. thesis

    https://www.mlmi.eng.cam.ac.uk/files/burt_thesis.pdf
    6 Nov 2019: plotted for a synthetic data set with N = 200, x N(0,52) and s = 5. ... 1.2 that holds for large N plotted for a syntheticdata set with N = 200, x N(0,52) and s = 5.
  13. Investigating Inference in BayesianNeural Networks via Active…

    https://www.mlmi.eng.cam.ac.uk/files/riccardo_barbano_dissertation_mlmi.pdf
    18 Nov 2019: Initially, we train on200 labelled data-points, and progress in batches of 50 with a budget of 200. ... 200 epochs are used to guarantee convergence. 40. 7 A More Complex Dataset.
  14. Pathologies of Deep Sparse Gaussian Process Regression

    https://www.mlmi.eng.cam.ac.uk/files/diaz_thesis.pdf
    30 Oct 2019: Pathologies of Deep SparseGaussian Process Regression. Sergio Pascual Díaz. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Fitzwilliam College August 2017. Declaration. I,
  15. Overcoming Catastrophic Forgetting in Neural Machine Translation

    https://www.mlmi.eng.cam.ac.uk/files/kell_thesis.pdf
    6 Nov 2019: Overcoming Catastrophic Forgetting inNeural Machine Translation. Gregory Kell. Department of Engineering. University of Cambridge. This dissertation is submitted for the degree of. MPhil Machine Learning Speech and Language Technology. Wolfson
  16. Tradeoffs in Neural Variational Inference

    https://www.mlmi.eng.cam.ac.uk/files/cruz_dissertation.pdf
    30 Oct 2019: The celebA dataset ([39]) consists of more than 200,000 images of celebrity faces. ... For ourwork, we consider 200,000 of these which we split as follows:. •
  17. Improving Sample Efficiency forGradient-based Policy Optimisation;…

    https://www.mlmi.eng.cam.ac.uk/files/wang_dissertation.pdf
    30 Oct 2019: Improving Sample Efficiency forGradient-based Policy Optimisation;. with an Application to Structured PolicyFunctions. Sihui Wang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy
  18. Extending and Applying the GaussianProcess Autoregressive Regression…

    https://www.mlmi.eng.cam.ac.uk/files/mlmi_thesis_justin_bunker.pdf
    18 Nov 2019: Extending and Applying the GaussianProcess Autoregressive Regression. Model. Justin Bunker. Supervisor:Dr. Richard E. Turner. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in
  19. Bayesian Neural Networks for K-Shot Learning

    https://www.mlmi.eng.cam.ac.uk/files/swiatkowski_dissertation.pdf
    30 Oct 2019: prior) 200.6 0.4GMM 1-mean (iso) 175.5 0.2. 1-.
  20. 1 Automatically Grading Learners’ English using a Deep Gaussian ...

    https://www.mlmi.eng.cam.ac.uk/files/sebastian_popescu_8224831_assignsubmission_file_sgp34_sebastiangabrielpopescu.pdf
    30 Oct 2019: 1. Automatically Grading Learners’. English using a Deep Gaussian Process. Sebastian Gabriel Popescu. Department of Engineering. University of Cambridge. A dissertation submitted to the University of Cambridge in partial. fulfilment of the
  21. Bayes By Backprop Neural Networks forDialogue Management Christopher…

    https://www.mlmi.eng.cam.ac.uk/files/tegho_dissertation.pdf
    30 Oct 2019: Bayes By Backprop Neural Networks forDialogue Management. Christopher Tegho. Queens’ College. MPhil Machine Learning,Speech and Language Technology. August 11th, 2017Cambridge University. I, Christopher Tegho of Queens’ college, being a
  22. Hierarchical Dialogue Management

    https://www.mlmi.eng.cam.ac.uk/files/gordaniello_dissertation.pdf
    30 Oct 2019: Hierarchical Dialogue Management. Francesca Giordaniello. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Pembroke College 11 August 2017. Declaration. I, Francesca Giordaniello
  23. Gong_dissertation

    https://www.mlmi.eng.cam.ac.uk/files/gong_dissertation_reduced.pdf
    30 Oct 2019: Wasserstein Generative AdversarialNetwork. Wenbo Gong. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Gonville and Caius College August 2017. I would like to dedicate this
  24. Neural Network Compression

    https://www.mlmi.eng.cam.ac.uk/files/okz21_thesisfinal.pdf
    6 Nov 2019: 0.5. 1. e) Soft-targets: T = 200. 0.5. 1. f) Soft-targets: T = 500.
  25. Bayesian Deep Generative Models for Semi-Supervised and Active…

    https://www.mlmi.eng.cam.ac.uk/files/gordon_dissertation.pdf
    30 Oct 2019: Bayesian Deep Generative Models forSemi-Supervised and Active Learning. Jonathan Gordon. Supervisor: Dr José Miguel Hernández-Lobato. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of
  26. Combining Sum Product Networks and Variational Autoencoders

    https://www.mlmi.eng.cam.ac.uk/files/thesis_pingliangtan.pdf
    6 Nov 2019: Combining Sum Product Networks andVariational Autoencoders. Ping Liang Tan. Supervisor: Dr Robert Peharz. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMasters of Philosphy. Hughes Hall August
  27. Sample efficient deep reinforcement learning for dialogue systems…

    https://www.mlmi.eng.cam.ac.uk/files/weisz_dissertation.pdf
    30 Oct 2019: Sample efficient deep reinforcementlearning for dialogue systems with large. action spaces. Gellért Weisz. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Churchill College 10
  28. 3D Human Motion Synthesis with Recurrent Gaussian Processes

    https://www.mlmi.eng.cam.ac.uk/files/mphil_thesis_yeziwei_wang.pdf
    6 Nov 2019: 3D Human Motion Synthesis withRecurrent Gaussian Processes. Yeziwei Wang. Supervisor: Dr. Zhenwen Dai. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Clare College August 2018.
  29. Probabilistic Bellman Consistency in Reinforcement Learning

    https://www.mlmi.eng.cam.ac.uk/files/biggio_dissertation.pdf
    18 Nov 2019: These scores are obtained by training each agentfor 200 million frames.
  30. BachBot: Automatic composition in thestyle of Bach chorales…

    https://www.mlmi.eng.cam.ac.uk/files/feynman_liang_8224771_assignsubmission_file_liangfeynmanthesis.pdf
    30 Oct 2019: BachBot: Automatic composition in thestyle of Bach chorales. Developing, analyzing, and evaluating a deep LSTM modelfor musical style. Feynman Liang. Department of EngineeringUniversity of Cambridge. M.Phil in Machine Learning, Speech, and Language
  31. Fact-Checking Fake News Bart Melman Supervisors:Dr Marcus Tomalin,…

    https://www.mlmi.eng.cam.ac.uk/files/2019_08_12_final_report_0.pdf
    18 Nov 2019: Fact-Checking Fake News. Bart Melman. Supervisors:Dr Marcus Tomalin,. Prof. Bill Byrne. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine
  32. thesis_1

    https://www.mlmi.eng.cam.ac.uk/files/mlsalt_thesis_yixuan_su.pdf
    6 Nov 2019: Relation Classification based on DeepLearning Approach. Yixuan Su. Department of EngineeringUniversity of Cambridge. MPhil in Machine Learning, Speech and Language TechnologyMaster of Philosophy. Selwyn College August 2018. I would like to dedicate
  33. Understanding Uncertainty in Bayesian Neural Networks

    https://www.mlmi.eng.cam.ac.uk/files/mphil_thesis_javier_antoran.pdf
    18 Nov 2019: Understanding Uncertainty in BayesianNeural Networks. Javier Antorán Cabiscol. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.
  34. One-shot Learning in DiscriminativeNeural Networks Jordan Burgess…

    https://www.mlmi.eng.cam.ac.uk/files/jordan_burgess_8224871_assignsubmission_file_burgess_jordan_thesis1.pdf
    30 Oct 2019: One-shot Learning in DiscriminativeNeural Networks. Jordan Burgess. Queens’ College. A dissertation submitted to the University of Cambridgein partial fulfilment of the requirements for the degree ofMaster of Philosophy in Machine Learning, Speech
  35. 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: Probabilistic Programming in JuliaNew Inference Algorithms. Kai Xu. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Homerton College August 2016. Declaration. I Kai Xu of
  36. Compression without Quantization Gergely Flamich Department of…

    https://www.mlmi.eng.cam.ac.uk/files/compression_without_quantization_flamich_reduced.pdf
    18 Nov 2019: However, if we used different sized images during training, it would be less justi-fied to set the same average code budget for, say, a 200 300 pixel image and a
  37. ALTA Project - Spoken Language Assessment and Learning

    https://www.mlmi.eng.cam.ac.uk/files/junjie_pan_8224791_assignsubmission_file_junjie_pan_dissertation_jp697.pdf
    30 Oct 2019: ALTA Project - Spoken LanguageAssessment and Learning. Improve Adaptation Performance of ASR to Non-NativeSpeakers. Junjie Pan. Department of EngineeringUniversity of Cambridge. M.Phil in Machine Learning, Speech and Language Technology. This
  38. Extending Deep GPs: Novel Variational Inference Schemes and a GPU…

    https://www.mlmi.eng.cam.ac.uk/files/maximilian_chamberlin_8224701_assignsubmission_file_mc.pdf
    30 Oct 2019: Extending Deep GPs: Novel VariationalInference Schemes and a GPU. Implementation. Maximilian Ekanem ChamberlinDepartment of Engineering. M.Phil in Machine Learning, Speech and Language Technology. This dissertation is submitted for the degree of.
  39. Islam Riashat MPhil MLSALT Dissertation

    https://www.mlmi.eng.cam.ac.uk/files/riashat_islam_8224811_assignsubmission_file_islam_riashat_mphil_mlsalt_dissertation.pdf
    30 Oct 2019: Active Learning for High DimensionalInputs using Bayesian Convolutional. Neural Networks. Riashat Islam. Department of Engineering. University of CambridgeM.Phil in Machine Learning, Speech and Language Technology. This dissertation is submitted for

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