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2020 – today
- 2024
[j4]Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic:
How does over-squashing affect the power of GNNs? Trans. Mach. Learn. Res. 2024 (2024)- 2023
- [j3]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:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j2]Andreea Deac, Theophane Weber, George Papamakarios:
Equivariant MuZero. Trans. Mach. Learn. Res. 2023 (2023) - [c7]Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan:
The Second Learning on Graphs Conference: Preface. LoG 2023: i-xix - [i15]Andreea Deac, Théophane Weber, George Papamakarios:
Equivariant MuZero. CoRR abs/2302.04798 (2023) - [i14]Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic:
How does over-squashing affect the power of GNNs? CoRR abs/2306.03589 (2023) - [i13]Andreea Deac, Jian Tang:
Evolving Computation Graphs. CoRR abs/2306.12943 (2023) - [i12]Marco Pegoraro, Clémentine Dominé, Emanuele Rodolà, Petar Velickovic, Andreea Deac:
Geometric Epitope and Paratope Prediction. CoRR abs/2307.13608 (2023) - 2022
- [c6]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:
A Generalist Neural Algorithmic Learner. LoG 2022: 2 - [c5]Andreea Deac, Marc Lackenby, Petar Velickovic:
Expander Graph Propagation. LoG 2022: 38 - [c4]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. LoG 2022: 54 - [c3]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:
The First Learning on Graphs Conference: Preface. LoG 2022: i-xxiii - [i11]Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic:
A Generalist Neural Algorithmic Learner. CoRR abs/2209.11142 (2022) - [i10]Andreea Deac, Marc Lackenby, Petar Velickovic:
Expander Graph Propagation. CoRR abs/2210.02997 (2022) - [i9]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. CoRR abs/2211.15839 (2022) - 2021
- [c2]Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic:
Neural Algorithmic Reasoners are Implicit Planners. NeurIPS 2021: 15529-15542 - [c1]Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang:
How to transfer algorithmic reasoning knowledge to learn new algorithms? NeurIPS 2021: 19500-19512 - [i8]Alice Del Vecchio, Andreea Deac, Pietro Liò, Petar Velickovic:
Neural message passing for joint paratope-epitope prediction. CoRR abs/2106.00757 (2021) - [i7]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:
Large-scale graph representation learning with very deep GNNs and self-supervision. CoRR abs/2107.09422 (2021) - [i6]Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic:
Neural Algorithmic Reasoners are Implicit Planners. CoRR abs/2110.05442 (2021) - [i5]Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang:
How to transfer algorithmic reasoning knowledge to learn new algorithms? CoRR abs/2110.14056 (2021) - 2020
- [i4]Andreea Deac, Pierre-Luc Bacon, Jian Tang:
Graph neural induction of value iteration. CoRR abs/2009.12604 (2020) - [i3]Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic:
XLVIN: eXecuted Latent Value Iteration Nets. CoRR abs/2010.13146 (2020)
2010 – 2019
- 2019
- [j1]Andreea Deac, Petar Velickovic, Pietro Sormanni:
Attentive Cross-Modal Paratope Prediction. J. Comput. Biol. 26(6): 536-545 (2019) - [i2]Andreea Deac, Yu-Hsiang Huang, Petar Velickovic, Pietro Liò, Jian Tang:
Drug-Drug Adverse Effect Prediction with Graph Co-Attention. CoRR abs/1905.00534 (2019) - 2018
- [i1]Andreea Deac, Petar Velickovic, Pietro Sormanni:
Attentive cross-modal paratope prediction. CoRR abs/1806.04398 (2018)
Coauthor Index
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last updated on 2024-10-07 22:09 CEST by the dblp team
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