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Incorporating Vision Encoders into Retrieval Augmented Visual…
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/visual_question_answering_nikolic.pdf24 Nov 2023: Incorporating Vision Encoders intoRetrieval Augmented Visual Question. Answering. Kristina Nikolić. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and -
Breaking the Limits of Diffusion Models via Continuous Dynamical…
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/breaking_the_limits_of_diffusion_models.pdf14 Nov 2023: 24. 3.3 Illustration of our custom ODE block capturing continuous-time dynamics.The block processes outputs from the derivative function approximator anduses them to delineate the data’s evolutionary trajectory. -
Well-Calibrated Bayesian NeuralNetworks On the empirical assessment…
https://www.mlmi.eng.cam.ac.uk/files/jheek_thesis.pdf6 Nov 2019: 𝜃)𝑞𝜙(𝜃) ]. (2.24). 5More generally, the argument that follows holds for any family of distributions 𝑞𝜙(𝜃) where the entropy𝔼[ log 𝑞𝜙(𝜃)] is invariant w.r.t. ... the global reparameterisation trick (2.23).Alternatively, -
Efficiently-Parametrised Approximate Posteriors in Pseudo-Point…
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/efficiently_parametrized_approximate_posteriors.pdf15 Nov 2021: exp(L1)p(u)q(u)q(u). du. (L1 log p(u)log q(u))q(u)du. = Eq(u) (L1 log p(u)log q(u)) L2 (2.24). ... L2 in Hensman et al. (2013) as follows (see equation 2.24 and 2.20 for the definition of L2and L1 respectively):. -
Contrastive Self-Supervised Learning for Tabular Data
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/contrastive_self-supervised_learning.pdf9 Dec 2021: Contrastive Self-Supervised Learningfor Tabular Data. Hugh Bishop. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Wolfson College -
Extending Deep GPs: Novel Variational Inference Schemes and a GPU…
https://www.mlmi.eng.cam.ac.uk/files/maximilian_chamberlin_8224701_assignsubmission_file_mc.pdf30 Oct 2019: 24. Chapter 1. Introduction: The Deep GaussianProcess Model. 1.1 What are Deep GPs? -
Knowledge Distillation for End-to-End Automatic Speech Recognition
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/knowledge_distillation_for_end-to-end_asr.pdf9 Dec 2021: 24. xii Table of contents. 3.2.1 Frame-level KD in CTC. 243.2.2 Sequence-level KD in CTC. ... However, the definition of. 24 Knowledge Distillation in ASR. "knowledge" varies from area to area. -
Variable length word encodings forneural translation models Jiameng…
https://www.mlmi.eng.cam.ac.uk/files/jiameng_gao_8224881_assignsubmission_file_j_gao_mphil_dissertation.pdf30 Oct 2019: the best MCR in Cambridge. I’ve absolutely loved 24 Parkside, everyone here had made. ... h, ,i (2.24). Where is a non-terminal symbol, while , 2 (X [ V) are a string of terminalsand non-terminals in the source and target languages respectively, where -
Graph Neural Stochastic Differential Equations
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/graph_neural_stochastic_differential_equations.pdf17 Nov 2023: 2.3.6 Comparison: Oversmoothing in GN-ODE vs. Standard GNN. 24. 3 Graph Neural Stochastic Differential Equations 26. ... 24. 3.1 The left image illustrates the political compass of voters while the rightimage presents their social circles, with colors -
ALTA Project - Spoken Language Assessment and Learning
https://www.mlmi.eng.cam.ac.uk/files/junjie_pan_8224791_assignsubmission_file_junjie_pan_dissertation_jp697.pdf30 Oct 2019: Its loss function is:. loss(H,Hre f ) = #(Corrections) #(Insertions) = A(H,Hre f ) (2.24). ... BLXXXtrn04 442 Spanish(100%) 26.53BLXXXeval1 223 Gujarati(100%) 24.11BLXXXeval2 220 Spanish(100%) 24.68. BLXXXeval3 226Dutch(14.6%), Polish(17.7%), French(16.4%
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