2021 - 2022 Course Highlights DissertationsMachine Learning:Attention-Based Sheaf Neural NetworksAutoregressive Conditional Neural ProcessesBetter Encoders for Neural Process Family ModelsBeyond Independent Masking in Tabular Self-SupervisionDeep Reinforcement Learning for 3D Molecular DesignDomain Generalization for Robust Model-Based Offline Reinforcement LearningGlobal Inducing Point Variational Approximations for Federated Bayesian Neural NetworksGraph Representation Learning for Child Mental Health PredictionImproving Machine Learning Systems by Eliciting and Incorporating Additional Human KnowledgeNon-Gaussian Lévy Processes in Machine LearningOutlier Detection with Hierarchical VAEs and Hamiltonian Monte CarloScalable Bayesian Inference for Probabilistic Spectrotemporal Models of Ia SupernovaeStochastic Memory for Sequence Models Speech and Language Processing:Automating Counterspeech in Dialogue SystemsBuilding a Conversational User Simulator using GANsEffectiveness of SSL Representations for Source SeparationJoint Learning of Practical Dialogue Systems and User SimulatorsMultimodal Coreference ResolutionVision Encoders in Visual Question Answering Computer Vision:Understanding and Fixing the Modality Gap in Vision-Language Models Posters from the Advanced Machine Learning ModuleConditional Neural ProcessesFew-Shot Learning with Novel MetricsFirst-Order Approximations for Efficient Meta-LearningImportance Weighted Auto EncodersMeta-Learning Approaches for Regression, Classification and Graph Representation LearningTowards a Neural StatisticianVariational Continual LearningWeight Uncertainty in Neural Networks