Text to Image Synthesis Using Generative Adversarial Networks. - Cristian Bodnar (CoRR, 2018)

Proximal Distilled Evolutionary Reinforcement Learning. - Cristian Bodnar; Ben Day; Pietro Lió (AAAI, 2020)

On Second Order Behaviour in Augmented Neural ODEs. - Alexander Norcliffe; Cristian Bodnar; Ben Day; Nikola Simidjievski; Pietro Lió (NeurIPS, 2020)

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping. - Cristian Bodnar; Adrian Li; Karol Hausman; Peter Pastor; Mrinal Kalakrishnan (Robotics: Science and Systems, 2020)

The Role of Isomorphism Classes in Multi-Relational Datasets. - Vijja Wichitwechkarn; Ben Day; Cristian Bodnar; Matthew Wales; Pietro Liò (CoRR, 2020)

A Geometric Perspective on Self-Supervised Policy Adaptation. - Cristian Bodnar; Karol Hausman; Gabriel Dulac-Arnold; Rico Jonschkowski (CoRR, 2020)

Neural ODE Processes. - Alexander Norcliffe; Cristian Bodnar; Ben Day; Jacob Moss; Pietro Liò (ICLR, 2021)

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. - Cristian Bodnar; Fabrizio Frasca; Yuguang Wang 001; Nina Otter; Guido F. Montúfar; Pietro Lió; Michael M. Bronstein (ICML, 2021)

Weisfeiler and Lehman Go Cellular: CW Networks. - Cristian Bodnar; Fabrizio Frasca; Nina Otter; Yuguang Wang 001; Pietro Liò; Guido F. Montúfar; Michael M. Bronstein (NeurIPS, 2021)

Deep Graph Mapper: Seeing Graphs Through the Neural Lens. - Cristian Bodnar; Catalina Cangea; Pietro Liò (Frontiers Big Data, 2021)

A Metric Space Perspective on Self-Supervised Policy Adaptation. - Cristian Bodnar; Karol Hausman; Gabriel Dulac-Arnold; Rico Jonschkowski (IEEE Robotics Autom. Lett., 2021)

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. - Cristian Bodnar; Francesco Di Giovanni; Benjamin Paul Chamberlain; Pietro Lió; Michael M. Bronstein (NeurIPS, 2022)

Sheaf Neural Networks with Connection Laplacians. - Federico Barbero; Cristian Bodnar; Haitz Sáez de Ocáriz Borde; Michael M. Bronstein; Petar Velickovic; Pietro Liò (TAG-ML, 2022)

Simplicial Attention Networks. - Christopher Wei Jin Goh; Cristian Bodnar; Pietro Liò (CoRR, 2022)

On the Expressive Power of Geometric Graph Neural Networks. - Chaitanya K. Joshi; Cristian Bodnar; Simon V. Mathis; Taco Cohen; Pietro Lio (ICML, 2023)

Sheaf-based Positional Encodings for Graph Neural Networks. - Yu He; Cristian Bodnar; Pietro Liò (NeurReps, 2023)

CIN++: Enhancing Topological Message Passing. - Lorenzo Giusti; Teodora Reu; Francesco Ceccarelli; Cristian Bodnar; Pietro Liò (CoRR, 2023)

Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation. - Jialin Chen; Yuelin Wang; Cristian Bodnar; Rex Ying; Pietro Lio; Yuguang Wang 001 (CoRR, 2023)

Topological Message Passing for Higher - Order and Long - Range Interactions. - Lorenzo Giusti; Teodora Reu; Francesco Ceccarelli; Cristian Bodnar; Pietro Liò (IJCNN, 2024)

Aurora: A Foundation Model of the Atmosphere. - Cristian Bodnar; Wessel P. Bruinsma; Ana Lucic; Megan Stanley; Johannes Brandstetter; Patrick Garvan; Maik Riechert; Jonathan A. Weyn; Haiyu Dong; Anna Vaughan; Jayesh K. Gupta; Kit Thambiratnam; et al. (CoRR, 2024)

A foundation model for the Earth system. - Cristian Bodnar; Wessel P. Bruinsma; Ana Lucic; Megan Stanley; Anna Allen; Johannes Brandstetter; Patrick Garvan; Maik Riechert; Jonathan A. Weyn; Haiyu Dong; Jayesh K. Gupta; Kit Thambiratnam; et al. (Nat., 2025)