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  2. Graph Neural Stochastic Differential Equations

    https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/graph_neural_stochastic_differential_equations.pdf
    17 Nov 2023: Graph Neural Stochastic DifferentialEquations. Richard Bergna. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Clare Hall August
  3. Eliciting Latent Knowledge from Language Reward Models

    https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/eliciting_latent_knowledge_from_language_reward_models_0.pdf
    17 Nov 2023: Eliciting Latent Knowledge fromLanguage Reward Models. Augustas Macijauskas. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.
  4. 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.pdf
    24 Jan 2022: Surgery PainkillersOld 25/40 = 62.5% 120/180 = 66.7%. Young 140/160 = 87.5% 18/20 = 90%Total 165/200 = 82.5% 138/200 = 69%. ... If we estimate the ˆATE: 165/200-138/200=13.5%, it erroneously draws that surgeryis more effective than painkillers.
  5. Vision Encoders in Visual Question Answering

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/vision_encoders_in_visual_question_answering.pdf
    9 Dec 2022: Vision Encoders in Visual QuestionAnswering. Ryan Anderson. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Magdalene College August 2022. Dedicated to my Mom, my brothers, and
  6. Controlling Hallucination while Generating Text from Structured Data…

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/controlling_hallucination_while_generating_text.pdf
    24 Jan 2022: 200) examples (Z. Chen, Eavani, W. Chen,et al., 2020). 10. 2.1.3 Transformers & Attention.
  7. Deep Reinforcement Learning for 3D Molecular Design

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/deep_reinforcement_learning_with_3d_molecular_design.pdf
    25 Nov 2022: Deep Reinforcement Learningfor 3D Molecular Design. Adrian Salovaara Black. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Homerton
  8. 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
  9. Domain Generalisation for Robust Model-Based Offline Reinforcement…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/domain_generalisation_for_robust_model_based_offline_rl_0.pdf
    1 Dec 2022: Domain Generalisation for RobustModel-Based Offline Reinforcement. LearningMLMI MPhil 2021-22. Alan Clark. Supervisor: Dr. David Krueger. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of
  10. 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.pdf
    24 Nov 2023: Large Language Models for ReliableInformation Extraction. Lukas Baliunas. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Churchill
  11. Global Inducing Point Posterior Approximations for Federated Bayesian …

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/global_inducing_point_posterior_approximations_for_federated_bnns.pdf
    25 Nov 2022: Global Inducing Point PosteriorApproximations for FederatedBayesian Neural Networks. Maximiliaan Olivier Jean Bronckers. Supervisors: Prof. Richard TurnerMatthew Ashman. Department of EngineeringUniversity of Cambridge. This dissertation is

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