Catalina Cangea

According to our database, Catalina Cangea authored at least 20 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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

2022

Goal-Conditioned Reinforcement Learning in the Presence of an Adversary.

Carlos Purves, Pietro Liò, Catalina Cangea

CoRR, 2022

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, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel

Proceedings of the International Conference on Machine Learning, 2022

2021

Exploiting multimodality and structure in world representations.

Catalina Cangea

PhD thesis, 2021

Deep Graph Mapper: Seeing Graphs Through the Neural Lens.

Cristian Bodnar, Catalina Cangea, Pietro Liò

Frontiers Big Data, 2021

Structure-aware generation of drug-like molecules.

Pavol Drotár, Arian Rokkum Jamasb, Ben Day, Catalina Cangea, Pietro Liò

CoRR, 2021

Generative Compositional Augmentations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification.

Catalina Cangea, Petar Velickovic, Pietro Liò

IEEE Trans. Neural Networks Learn. Syst., 2020

Message Passing Neural Processes.

Ben Day, Catalina Cangea, Arian R. Jamasb, Pietro Liò

CoRR, 2020

Generative Graph Perturbations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

CoRR, 2020

Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks.

Péter Mernyei, Catalina Cangea

CoRR, 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

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

The PlayStation Reinforcement Learning Environment (PSXLE).

Carlos Purves, Catalina Cangea, Petar Velickovic

CoRR, 2019

Spatio-Temporal Deep Graph Infomax.

Felix L. Opolka, Aaron Solomon, Catalina Cangea, Petar Velickovic, Pietro Liò, R. Devon Hjelm

CoRR, 2019

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering.

Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville

Proceedings of the Visually Grounded Interaction and Language (ViGIL), 2019

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering.

Catalina Cangea, Eugene Belilovsky, Aaron C. Courville

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Structure-Based Networks for Drug Validation.

Catalina Cangea, Arturas Grauslys, Pietro Liò, Francesco Falciani

CoRR, 2018

Towards Sparse Hierarchical Graph Classifiers.

Catalina Cangea, Petar Velickovic, Nikola Jovanovic, Thomas Kipf, Pietro Liò

CoRR, 2018

2017

XFlow: 1D-2D Cross-modal Deep Neural Networks for Audiovisual Classification.

Catalina Cangea, Petar Velickovic, Pietro Liò

CoRR, 2017