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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.

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.

1 Feb 2021: Figure 3: Left: We provide the model with 1, 40, 200 and 784 context points(top row) and query the entire image.

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.

30 Oct 2019: 0. 50. 100. 150. 200. 250. 300. Reward. Learning Curve for Swimmer.

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).

14 Dec 2023: Stability Analysis and Mutual Information. 0 100 200 300 400 500 600 700Iteration. ... networks in our Info-WGAN for MNIST. 0 200 400 600 800 1000Iteration.

15 Nov 2019: quick. Fever Challenge. DataCorpus 6 million Wikipedia pagesTraining Set 200 thousand claims.

21 Jan 2022: For best results, all graphic elements should be at least 150-200 pixels per inch in their final printed size. ... If you are laying out a large poster and using half-scale dimensions, be sure to preview your graphics at 200% to see them at their final

17 May 2022: Datasets consist of 200 samples from either an Exponential, Gaussian, Uniform orLaplacian distribution with equal probability. ... 200 coordinates sampled, 20-sample summaries. The model is: Unsupervised, data efficient, parameter efficient, capable of

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

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.

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

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.

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.

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 Dec 2023: of arollout for different neural constraints over 200 rollouts with 300 environ-ments each. ... 59. 5.10 Mean reward over 200 rollouts across 300 steps per rollout.

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,

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

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:. •

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 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

30 Oct 2019: prior) 200.6 0.4GMM 1-mean (iso) 175.5 0.2. 1-.

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

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

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

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 Nov 2023: For example, if we’re considering 2-dimensional space,dx = 2 and feature-map resolution a = 200, and b = 64 CNN channels, each featuremap consists of 200200 values, and h(i)

6 Nov 2019: 0.5. 1. e) Soft-targets: T = 200. 0.5. 1. f) Soft-targets: T = 500.

15 Nov 2021: Depth Uncertainty Networks forActive Learning. Chelsea Murray. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Corpus Christi

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

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

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

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.

18 Nov 2019: These scores are obtained by training each agentfor 200 million frames.

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

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

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

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.

14 Nov 2023: Data Compression with VariationalImplicit Neural Representations. Jiajun He. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.

25 Nov 2022: This lead to a training time of 200 epochs. We set the corruptionparameter p = 0.3, as opposed to the default of value of 0.5 used elsewhere, due to the

11 Feb 2021: During training,the newbob learning rate scheduler with an initial learning rate of 5 105 was used, andbatch size was set to 200.

24 Nov 2023: Optimal PAC-Bayes Bounds and theirVariational Approximations. Szilvia Ujváry. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.

21 Jan 2022: MPhil in Machine Learning and Machine IntelligenceCambridge University Department of Engineering. Continuity of autoencoders, unsupervised anomalydetection and Deep Atlases. Dissertation submitted by. Charles A. ArnalHomerton College. August 2021.

15 Nov 2021: A Policy Agnostic Framework for PostHoc Analysis of Organ Allocation. Policies. Agathe de Vulpian. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. in Machine Learning and

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

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

11 Feb 2021: Improved Ergodic Inference via. Kernelised Stein Discrepancy. Wenlong Chen. Darwin College. This dissertation is submitted on August 19, 2020 for the degree of Master of. Philosophy in Machine Learning and Machine Intelligence. Declaration. I,

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

15 Nov 2021: We briefly trialled a custom architecture – a multi-layer perceptron consisting of threehidden layers with ReLU activations, 200 units each and batch normalisation after every fully-connected layer.