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Andreea Deac
Andreea Deac
Isomorphic Labs
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Title
Cited by
Cited by
Year
Scientific discovery in the age of artificial intelligence
H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ...
Nature 620 (7972), 47-60, 2023
8732023
Drug-Drug Adverse Effect Prediction with Graph Co-Attention
A Deac, YH Huang, P Veličković, P Liò, J Tang
arXiv preprint arXiv:1905.00534, 2019
1002019
Expander graph propagation
A Deac, M Lackenby, P Veličković
Learning on Graphs Conference, 38: 1-38: 18, 2022
712022
A generalist neural algorithmic learner
B Ibarz, V Kurin, G Papamakarios, K Nikiforou, M Bennani, R Csordás, ...
Learning on Graphs Conference, 2: 1-2: 23, 2022
682022
Attentive cross-modal paratope prediction
A Deac, P Veličković, P Sormanni
Journal of Computational Biology 26 (6), 536-545, 2019
662019
Large-scale graph representation learning with very deep GNNs and self-supervision
R Addanki, PW Battaglia, D Budden, A Deac, J Godwin, T Keck, WLS Li, ...
arXiv preprint arXiv:2107.09422, 2021
322021
How to transfer algorithmic reasoning knowledge to learn new algorithms?
LP Xhonneux, AI Deac, P Veličković, J Tang
Advances in Neural Information Processing Systems 34, 19500-19512, 2021
312021
Neural message passing for joint paratope-epitope prediction
A Del Vecchio, A Deac, P Liò, P Veličković
ICML Workshop on Computational Biology 2021, 2021
292021
Neural Algorithmic Reasoners are Implicit Planners
A Deac, P Veličković, O Milinković, PL Bacon, J Tang, M Nikolic
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
222021
XLVIN: eXecuted Latent Value Iteration Nets
A Deac, P Veličković, O Milinković, PL Bacon, J Tang, M Nikolić
arXiv preprint arXiv:2010.13146, 2020
202020
How does over-squashing affect the power of GNNs?
F Di Giovanni, TK Rusch, MM Bronstein, A Deac, M Lackenby, S Mishra, ...
arXiv preprint arXiv:2306.03589, 2023
192023
Continuous Neural Algorithmic Planners
Y He, P Veličković, P Liò, A Deac
Learning on Graphs Conference, 54: 1-54: 13, 2022
102022
How does over-squashing affect the power of gnns
T Francesco Di Giovanni, K Rusch, MM Bronstein, A Deac, M Lackenby, ...
arXiv preprint arXiv:2306.03589 4, 2023
92023
Graph neural induction of value iteration
A Deac, PL Bacon, J Tang
ICML GRL+ 2020, 2020
92020
Neural message passing for joint paratope-epitope prediction
AD Vecchio, A Deac, P Liò, P Veličković
52021
Structured Multi-View Representations for Drug Combinations
S Liu, A Deac, Z Zhu, J Tang
Machine Learning for Molecules Workshop, NeurIPS 2020, 2020
52020
Geometric epitope and paratope prediction
M Pegoraro, C Dominé, E Rodolà, P Veličković, A Deac
Bioinformatics 40 (7), 2024
32024
Evolving Computation Graphs
A Deac, J Tang
arXiv preprint arXiv:2306.12943, 2023
32023
Equivariant MuZero
A Deac, T Weber, G Papamakarios
arXiv preprint arXiv:2302.04798, 2023
12023
Empowering graph representation learning with paired training and graph co-attention
A Deac, YH Huang, P Velickovic, P Lio, J Tang
12020
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