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Understanding Uncertainty in Bayesian Neural Networks
https://www.mlmi.eng.cam.ac.uk/files/mphil_thesis_javier_antoran.pdf18 Nov 2019: The MNIST test set digits have been projected onto the latent space and are displayedwith a different colour per class. ... Fig. 2.8 MNIST test-set digits with pixels randomly dropped and corresponding VAEAC inpaintings. -
Fairness in Machine Learning withCausal Reasoning Philip Ball…
https://www.mlmi.eng.cam.ac.uk/files/ball_thesis.pdf6 Nov 2019: Fairness in Machine Learning withCausal Reasoning. Philip Ball. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning, Speech and Language. Technology. Sidney -
Sum-Product Copulas
https://www.mlmi.eng.cam.ac.uk/files/ramonacomanescu-thesis.pdf18 Nov 2019: SPNshave achieved competitive results on numerous tasks. A good test for deep architectures is that of image completion, where it is essential todetect deep structure. -
Multilingual Models in Neural Machine Translation
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/multilingual_models_in_neural_machine_translation.pdf24 Nov 2023: processing. 29. 4.5 Examples of translation hypotheses from the test set of WMT’21 Chinese-English. ... In this project, we test the impact of using 2 to 32 demonstrationexamples. -
Distributed Variational Inferenceand Privacy
https://www.mlmi.eng.cam.ac.uk/files/dissertation_-_xiping_liu.pdf18 Nov 2019: Distributed Variational Inferenceand Privacy. Xiping Liu. Supervisor: Dr Richard E. Turner. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine -
A Policy Agnostic Framework for Post Hoc Analysis of Organ Allocation …
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/framework_for_analysis_of_organ_allocation_policies.pdf15 Nov 2021: 12 Background. and their rapidity in test phase compared to competing kernel methods, the network is thenoptimized through gradient descent. -
Better Encoders for Neural Process Family Models
https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/better_encoders_for_neural_process_family_models.pdf6 Dec 2022: representation can be learnt. However, once meta-training has been performed, the test-. ... having the true observations passed through to make realistic predictions at test-time. -
thesis
https://www.mlmi.eng.cam.ac.uk/files/james_requeima_8224681_assignsubmission_file_requeimajamesthesis.pdf30 Oct 2019: 53. Chapter 1. Introduction. 1.1 Optimization. Optimization problems are widespread in science, engineering, economics and finance.For example, regional electricity grid system operators (ISOs) optimise the productionof electricity (solar, wind -
Interpretability for Conditional Average Treatment Effect Estimation
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/interpretability_for_conditional_average_treatment_effect_estimation_-_javier_abad.pdf24 Jan 2022: Introduction. Inferring the causal effect of interventions is a fundamental problem in many domains,including economics, education, and healthcare. -
Non-Gaussian Lévy Processes in Machine Learning
https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/non-gaussian_levy_processes_in_machine_learning_reduced.pdf25 Nov 2022: Non-Gaussian Lévy Processes inMachine Learning. Trevor Clark. Machine Learning and Machine IntelligenceDepartment of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Fitzwilliam College -
Large Language Models for Reliable Information Extraction
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/large_language_models_for_reliable_information_extraction.pdf24 Nov 2023: This dataset provides agood setting to test the ability of LLMs to comprehend non-trivial information. -
Joint Learning of Practical Dialogue Systems and User Simulators
https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/joint_learning_of_practical_dialogue_systems_and_user_simulators_reduced.pdf6 Dec 2022: US User Simulator. 3, 6. Chapter 1. Introduction. 1.1 Motivation. Language is a fundamentally important part of human intelligence, and is at the heart of many ofthe most important economic ... The full dataset contains approximately 10,400 dialogues, -
Mitigating Gender Bias in Dialogue Generation Gabrielle (Ming Yi) ...
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/mitigating_gender_bias_in_dialogue_generation.pdf15 Nov 2021: author noted that they cannot test the effectiveness of this method for gender bias because. Results that match 1 of 2 words
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Assessment | MPhil in Machine Learning and Machine Intelligence
https://www.mlmi.eng.cam.ac.uk/course-structure/assessment14 Jul 2024: These include unseen written tests, take-home tests, reports, practical write-ups, presentations, essays, demonstrations, or other exercises. -
Frequently Asked Questions | MPhil in Machine Learning and Machine…
https://www.mlmi.eng.cam.ac.uk/frequently-asked-questions14 Jul 2024: Q. Is a TOEFL test score sufficient for this programme or does each applicant need an IELTS test score? -
Academic Background | MPhil in Machine Learning and Machine…
https://www.mlmi.eng.cam.ac.uk/how-apply/academic-background14 Jul 2024: A mathematically focussed Economics degree can sometimes be suitable preparation. Students will be expected to have strong backgrounds in mathematics and computer programming, as well as practical skills for large-scale -
Weight Uncertainty in Neural Networks
https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_advanced_machine_learning_posters/weight_uncertainty_in_neural_networks_2.pdf14 Dec 2023: 50k/10k/10k data split, trained using SGD optimizer. Model # Units Test Error Test Error. ... Test error 1.58% 1.62% 1.75% 1.84%. Table 2. Classification error after weight pruning. -
Doubly Stochastic Variational Inference for Deep Gaussian Processes
https://www.mlmi.eng.cam.ac.uk/files/doubly_stochastic_variational_inference_for_deep_gaussian_process.pdf7 Jul 2020: Nn=1 p(yn|fn) where inference over. test locations x is. f(x)|y GP (kff (Kff σ2yI)1y,Kff kff (Kff σ2yI)1kff. ... Regression. Figure: Regression test log-likelihood results on benchmark UCI datasets. The plots show the mean standarddeviation over 20 -
Well-Calibrated Bayesian NeuralNetworks On the empirical assessment…
https://www.mlmi.eng.cam.ac.uk/files/jheek_thesis.pdf6 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. -
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.pdf6 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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