XFlow: 1D-2D Cross-modal Deep Neural Networks for Audiovisual Classification. - Catalina Cangea; Petar Velickovic; Pietro Liò (CoRR, 2017)

Towards Sparse Hierarchical Graph Classifiers. - Catalina Cangea; Petar Velickovic; Nikola Jovanovic 001; Thomas Kipf; Pietro Liò (CoRR, 2018)

Structure-Based Networks for Drug Validation. - Catalina Cangea; Arturas Grauslys; Pietro Liò; Francesco Falciani (CoRR, 2018)

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. - Catalina Cangea; Eugene Belilovsky; Aaron C. Courville (BMVC, 2019)

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. - Catalina Cangea; Eugene Belilovsky; Pietro Liò; Aaron C. Courville (ViGIL@NeurIPS, 2019)

Spatio-Temporal Deep Graph Infomax. - Felix L. Opolka; Aaron Solomon; Catalina Cangea; Petar Velickovic; Pietro Liò; R. Devon Hjelm (CoRR, 2019)

The PlayStation Reinforcement Learning Environment (PSXLE). - Carlos Purves; Catalina Cangea; Petar Velickovic (CoRR, 2019)

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (BMVC, 2020)

Sparse Dynamic Distribution Decomposition: Efficient Integration of Trajectory and Snapshot Time Series Data. - Jake P. Taylor-King; Cristian Regep; Jyothish Soman; Flawnson Tong; Catalina Cangea; Charlie Roberts (CoRR, 2020)

Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks. - Péter Mernyei; Catalina Cangea (CoRR, 2020)

Generative Graph Perturbations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (CoRR, 2020)

Message Passing Neural Processes. - Ben Day; Catalina Cangea; Arian R. Jamasb; Pietro Liò (CoRR, 2020)

XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. - Catalina Cangea; Petar Velickovic; Pietro Liò (IEEE Trans. Neural Networks Learn. Syst., 2020)

Generative Compositional Augmentations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (ICCV, 2021)

Structure-aware generation of drug-like molecules. - Pavol Drotár; Arian Rokkum Jamasb; Ben Day; Catalina Cangea; Pietro Liò (CoRR, 2021)

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

Exploiting multimodality and structure in world representations. - Catalina Cangea (2021)

General-purpose, long-context autoregressive modeling with Perceiver AR. - Curtis Hawthorne; Andrew Jaegle; Catalina Cangea; Sebastian Borgeaud; Charlie Nash; Mateusz Malinowski; Sander Dieleman; Oriol Vinyals; Matthew M. Botvinick; Ian Simon; Hannah Sheahan; Neil Zeghidour; et al. (ICML, 2022)

Goal-Conditioned Reinforcement Learning in the Presence of an Adversary. - Carlos Purves; Pietro Liò; Catalina Cangea (CoRR, 2022)

Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. - Jannik Kossen; Catalina Cangea; Eszter Vértes; Andrew Jaegle; Viorica Patraucean; Ira Ktena; Nenad Tomasev; Danielle Belgrave (Trans. Mach. Learn. Res., 2023)