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Auto-Encoding Variational BayesPawe l F. P. Budzianowski, Thomas F.…
https://www.mlmi.eng.cam.ac.uk/files/mlsalt4_budzianowski_nicholson_tebbutt.pdf30 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. -
Auto-Encoding Variational Bayes
https://www.mlmi.eng.cam.ac.uk/files/auto_encoding_var_bayes_d423c.pdf6 Nov 2019: 50. 100. 150. 200. 250. 300. Num. ber. of. dim. ensi. ... Squares of weights of dimensions. 0. 50. 100. 150. 200. 250. -
Auto-Encoding Variational Bayes
https://www.mlmi.eng.cam.ac.uk/files/e520t_auto_encoding_variational_bayes.pdf6 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. -
Structured Priors for Policy Optimisation
https://www.mlmi.eng.cam.ac.uk/files/structured-priors-policy_wang.pdf30 Oct 2019: 0. 50. 100. 150. 200. 250. 300. Reward. Learning Curve for Swimmer. -
Uncertainty in Bayesian Neural Networks
https://www.mlmi.eng.cam.ac.uk/files/uncertainty_in_bayesian_neural_networks_v2.pdf14 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). -
Fact Checking Fake News
https://www.mlmi.eng.cam.ac.uk/files/2019_06_17_poster_industry_presentation_bart_melman.pdf15 Nov 2019: quick. Fever Challenge. DataCorpus 6 million Wikipedia pagesTraining Set 200 thousand claims. -
Sequential Neural Models with Stochastic Layers
https://www.mlmi.eng.cam.ac.uk/files/d402k_poster_sequential_neural_models_with_stochastic_layers.pdf6 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 -
Curiosity-Driven Reinforcement Learning for Dialogue Management
https://www.mlmi.eng.cam.ac.uk/files/paulawesselmann_mlsalt.pdf6 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. -
MergedFile
https://www.mlmi.eng.cam.ac.uk/files/de_jong_thesis.pdf6 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 -
Designing Neural Network Hardware Accelerators Using Deep Gaussian…
https://www.mlmi.eng.cam.ac.uk/files/havasi_dissertation.pdf30 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.
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