Andreea Deac

According to our database, Andreea Deac authored at least 17 papers between 2019 and 2023.

Collaborative distances:

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

2023

Scientific discovery in the age of artificial intelligence.

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik

Nat., 2023

Geometric Epitope and Paratope Prediction.

Marco Pegoraro, Clémentine Dominé, Emanuele Rodolà, Petar Velickovic, Andreea Deac

CoRR, 2023

Evolving Computation Graphs.

Andreea Deac, Jian Tang

CoRR, 2023

How does over-squashing affect the power of GNNs?

Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic

CoRR, 2023

Equivariant MuZero.

Andreea Deac, Théophane Weber, George Papamakarios

CoRR, 2023

2022

The First Learning on Graphs Conference: Preface.

Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov

Proceedings of the Learning on Graphs Conference, 2022

A Generalist Neural Algorithmic Learner.

Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Joseph Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic

Proceedings of the Learning on Graphs Conference, 2022

Continuous Neural Algorithmic Planners.

Yu He, Petar Velickovic, Pietro Liò, Andreea Deac

Proceedings of the Learning on Graphs Conference, 2022

Expander Graph Propagation.

Andreea Deac, Marc Lackenby, Petar Velickovic

Proceedings of the Learning on Graphs Conference, 2022

2021

Large-scale graph representation learning with very deep GNNs and self-supervision.

Ravichandra Addanki, Peter W. Battaglia, David Budden, Andreea Deac, Jonathan Godwin, Thomas Keck, Wai Lok Sibon Li, Alvaro Sanchez-Gonzalez, Jacklynn Stott, Shantanu Thakoor, Petar Velickovic

CoRR, 2021

Neural message passing for joint paratope-epitope prediction.

Alice Del Vecchio, Andreea Deac, Pietro Liò, Petar Velickovic

CoRR, 2021

How to transfer algorithmic reasoning knowledge to learn new algorithms?

Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Algorithmic Reasoners are Implicit Planners.

Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

XLVIN: eXecuted Latent Value Iteration Nets.

Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic

CoRR, 2020

Graph neural induction of value iteration.

Andreea Deac, Pierre-Luc Bacon, Jian Tang

CoRR, 2020

2019

Attentive Cross-Modal Paratope Prediction.

Andreea Deac, Petar Velickovic, Pietro Sormanni

J. Comput. Biol., 2019

Drug-Drug Adverse Effect Prediction with Graph Co-Attention.

Andreea Deac, Yu-Hsiang Huang, Petar Velickovic, Pietro Liò, Jian Tang

CoRR, 2019