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Factorised Neural Relational Inference for Multi-Interaction Systems., , , and . CoRR, (2019)Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders., and . CoRR, (2019)A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth., , and . Frontiers Big Data, (2022)Incorporating network based protein complex discovery into automated model construction., , , , , , and . CoRR, (2020)Using ontology embeddings for structural inductive bias in gene expression data analysis., , , , , , and . CoRR, (2020)Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases., , , , , , , and . Bioinform., 38 (5): 1320-1327 (2022)Graph Representation Learning on Tissue-Specific Multi-Omics., , , , and . CoRR, (2021)Decoupling feature propagation from the design of graph auto-encoders., , , and . CoRR, (2019)Interpreting deep learning for cell differentiation: supervised and unsupervised models viewed through the lens of information and perturbation theory.. University of Cambridge, UK, (2019)British Library, EThOS.CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks., , , , and . Bioinform., 38 (5): 1277-1286 (2022)