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Meta-learning using privileged information for dynamics


Apr 29, 2021
Ben Day, Alexander Norcliffe, Jacob Moss, Pietro Liò

* Published as a workshop paper at the Learning to Learn and SimDL workshops at ICLR 2021. 4 pages, 3 pages of appendices 

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Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches


Apr 14, 2021
Dmitry Kazhdan, Botty Dimanov, Helena Andres Terre, Mateja Jamnik, Pietro Liò, Adrian Weller

* Presented at the RAI, WeaSul, and RobustML workshops at The Ninth International Conference on Learning Representations (ICLR) 2021 

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Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions


Apr 10, 2021
Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas D. Lane

* Short versions to appear at the GNNSys Workshop at MLSys 2021 and the Hardware-Aware Efficient Training Workshop at ICLR 2021 

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Neural ODE Processes


Mar 23, 2021
Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò

* To appear at ICLR 2021. 9 pages, 6 figures, 7 pages of appendices 

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An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering


Mar 05, 2021
Nikola Zubić, Pietro Liò

* 11 pages, 8 figures, 4 tables, to appear as a full paper with oral contribution in AIAI 2021 

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Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks


Mar 04, 2021
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael Bronstein

* 24 pages, 9 figures 

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Predicting Patient Outcomes with Graph Representation Learning


Jan 11, 2021
Emma Rocheteau, Catherine Tong, Petar Veličković, Nicholas Lane, Pietro Liò

* Accepted at the W3PHIAI-21 and DLG-AAAI'21 workshops at AAAI 2021 

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MEME: Generating RNN Model Explanations via Model Extraction


Dec 13, 2020
Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò

* Presented at the HAMLETS workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020) 

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Using ontology embeddings for structural inductive bias in gene expression data analysis


Nov 22, 2020
Maja Trębacz, Zohreh Shams, Mateja Jamnik, Paul Scherer, Nikola Simidjievski, Helena Andres Terre, Pietro Liò

* 4 pages + 2 page references, 15th Machine Learning in Computational Biology (MLCB) meeting, 2020 

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Now You See Me (CME): Concept-based Model Extraction


Oct 25, 2020
Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller

* Presented at the AIMLAI workshop at the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020) 

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Directional Graph Networks


Oct 06, 2020
Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò

* 8 pages, 10 pages appendix, 6 figures, subtitle: Anisotropic aggregation in graph neural networks via directional vector fields 

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The Role of Isomorphism Classes in Multi-Relational Datasets


Sep 30, 2020
Vijja Wichitwechkarn, Ben Day, Cristian Bodnar, Matthew Wales, Pietro Liò

* 7 pages main text, 1 page of references and an ethics statement, 3 pages of appendices 

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Incorporating network based protein complex discovery into automated model construction


Sep 29, 2020
Paul Scherer, Maja Trȩbacz, Nikola Simidjievski, Zohreh Shams, Helena Andres Terre, Pietro Liò, Mateja Jamnik

* 7 Pages, 2 Figures 

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Message Passing Neural Processes


Sep 29, 2020
Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò

* 18 pages, 6 figures. The first two authors contributed equally 

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Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit


Jul 18, 2020
Emma Rocheteau, Pietro Liò, Stephanie Hyland

* arXiv admin note: substantial text overlap with arXiv:2006.16109 

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RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow


Jul 08, 2020
Samuel Glass, Simeon Spasov, Pietro Liò

* To appear at ICML 2020, AutoML Workshop. Contains 11 pages, 5 figures 

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Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks


Jun 29, 2020
Emma Rocheteau, Pietro Liò, Stephanie Hyland

* 4 pages, HSYS2020 proceedings 

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Uncertainty in Neural Relational Inference Trajectory Reconstruction


Jun 25, 2020
Vasileios Karavias, Ben Day, Pietro Liò

* 4 main pages, 1 page of supplementary materials. Accepted for presentation at the Graph Representation Learning and Beyond workshop at ICML 2020 

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A Multiscale Graph Convolutional Network Using Hierarchical Clustering


Jun 22, 2020
Alex Lipov, Pietro Liò

* 5 pages, 2 figures, submitted as a GRL+ workshop paper for ICML 2020 

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Constraining Variational Inference with Geometric Jensen-Shannon Divergence


Jun 18, 2020
Jacob Deasy, Nikola Simidjievski, Pietro Liò


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On Second Order Behaviour in Augmented Neural ODEs


Jun 12, 2020
Alexander Norcliffe, Cristian Bodnar, Ben Day, Nikola Simidjievski, Pietro Liò

* Contains 27 pages, 14 figures 

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tvGP-VAE: Tensor-variate Gaussian Process Prior Variational Autoencoder


Jun 08, 2020
Alex Campbell, Pietro Liò

* 8 pages, 2 Figures 

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Kolmogorov Regularization for Link Prediction


Jun 07, 2020
Paris D. L. Flood, Ramon Viñas, Pietro Liò


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Neural Bipartite Matching


Jun 02, 2020
Dobrik Georgiev, Pietro Liò


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MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library


Apr 16, 2020
Dmitry Kazhdan, Zohreh Shams, Pietro Liò

* Presented at the KR2ML workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada 

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Principal Neighbourhood Aggregation for Graph Nets


Apr 12, 2020
Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Veličković


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Adaptive Prediction Timing for Electronic Health Records


Mar 05, 2020
Jacob Deasy, Ari Ercole, Pietro Liò


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Towards a predictive spatio-temporal representation of brain data


Feb 29, 2020
Tiago Azevedo, Luca Passamonti, Pietro Liò, Nicola Toschi

* To appear in the Workshop on AI for Affordable Healthcare (AI4AH) at ICLR 2020. 8 pages, 2 figures 

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Deep Graph Mapper: Seeing Graphs through the Neural Lens


Feb 20, 2020
Cristian Bodnar, Cătălina Cangea, Pietro Liò

* 13 pages, 10 figures 

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