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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
2342023
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
772019
Attentive cross-modal paratope prediction
A Deac, P Veličković, P Sormanni
Journal of Computational Biology 26 (6), 536-545, 2019
582019
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
422022
Expander graph propagation
A Deac, M Lackenby, P Veličković
Learning on Graphs Conference, 38: 1-38: 18, 2022
392022
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
272021
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
242021
Neural message passing for joint paratope-epitope prediction
A Del Vecchio, A Deac, P Liò, P Veličković
ICML Workshop on Computational Biology 2021, 2021
212021
XLVIN: eXecuted Latent Value Iteration Nets
A Deac, P Veličković, O Milinković, PL Bacon, J Tang, M Nikolić
arXiv preprint arXiv:2010.13146, 2020
182020
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
152021
Graph neural induction of value iteration
A Deac, PL Bacon, J Tang
ICML GRL+ 2020, 2020
92020
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
82023
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
62023
Structured Multi-View Representations for Drug Combinations
S Liu, A Deac, Z Zhu, J Tang
Machine Learning for Molecules Workshop, NeurIPS 2020, 2020
52020
Continuous Neural Algorithmic Planners
Y He, P Veličković, P Liò, A Deac
Learning on Graphs Conference, 54: 1-54: 13, 2022
42022
Neural message passing for joint paratope-epitope prediction
AD Vecchio, A Deac, P Liò, P Veličković
32021
Equivariant MuZero
A Deac, T Weber, G Papamakarios
arXiv preprint arXiv:2302.04798, 2023
12023
Geometric Epitope and Paratope Prediction
M Pegoraro, C Dominé, E Rodolà, P Veličković, A Deac
bioRxiv, 2023.06. 29.546973, 2023
12023
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention
A Deac, YH Huang, P Velickovic, P Lio, J Tang
12019
Reasoning with structure: graph neural networks algorithms and applications
AI Deac
2024
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