Search Results - "Deac, Andreea"

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

“…Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment and accelerate research, helping scientists to generate…”
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Geometric epitope and paratope prediction by Pegoraro, Marco, Dominé, Clémentine, Rodolà, Emanuele, Veličković, Petar, Deac, Andreea

“…Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal…”
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Publisher Correction: Scientific discovery in the age of artificial intelligence by Wang, Hanchen, Fu, Tianfan, Du, Yuanqi, Gao, Wenhao, Huang, Kexin, Liu, Ziming, Chandak, Payal, Liu, Shengchao, Van Katwyk, Peter, Deac, Andreea, Anandkumar, Anima, Bergen, Karianne, Gomes, Carla P., Ho, Shirley, Kohli, Pushmeet, Lasenby, Joan, Leskovec, Jure, Liu, Tie-Yan, Manrai, Arjun, Marks, Debora, Ramsundar, Bharath, Song, Le, Sun, Jimeng, Tang, Jian, Veličković, Petar, Welling, Max, Zhang, Linfeng, Coley, Connor W., Bengio, Yoshua, Zitnik, Marinka

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Evolving Computation Graphs by Deac, Andreea, Tang, Jian

“…Graph neural networks (GNNs) have demonstrated success in modeling relational data, especially for data that exhibits homophily: when a connection between…”
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Equivariant MuZero by Deac, Andreea, Weber, Théophane, Papamakarios, George

“…Deep reinforcement learning repeatedly succeeds in closed, well-defined domains such as games (Chess, Go, StarCraft). The next frontier is real-world…”
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Expander Graph Propagation by Deac, Andreea, Lackenby, Marc, Veličković, Petar

“…Deploying graph neural networks (GNNs) on whole-graph classification or regression tasks is known to be challenging: it often requires computing node features…”
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Geometric Epitope and Paratope Prediction by Pegoraro, Marco, Dominé, Clémentine, Rodolà, Emanuele, Veličković, Petar, Deac, Andreea

“…Antibody-antigen interactions play a crucial role in identifying and neutralizing harmful foreign molecules. In this paper, we investigate the optimal…”
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Continuous Neural Algorithmic Planners by He, Yu, Veličković, Petar, Liò, Pietro, Deac, Andreea

“…Neural algorithmic reasoning studies the problem of learning algorithms with neural networks, especially with graph architectures. A recent proposal, XLVIN,…”
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Graph neural induction of value iteration by Deac, Andreea, Bacon, Pierre-Luc, Tang, Jian

“…Many reinforcement learning tasks can benefit from explicit planning based on an internal model of the environment. Previously, such planning components have…”
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Neural message passing for joint paratope-epitope prediction by Del Vecchio, Alice, Deac, Andreea, Liò, Pietro, Veličković, Petar

“…Antibodies are proteins in the immune system which bind to antigens to detect and neutralise them. The binding sites in an antibody-antigen interaction are…”
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How does over-squashing affect the power of GNNs? by Di Giovanni, Francesco, Rusch, T. Konstantin, Bronstein, Michael M, Deac, Andreea, Lackenby, Marc, Mishra, Siddhartha, Veličković, Petar

“…Graph Neural Networks (GNNs) are the state-of-the-art model for machine learning on graph-structured data. The most popular class of GNNs operate by exchanging…”
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Attentive cross-modal paratope prediction by Deac, Andreea, Veličković, Petar, Sormanni, Pietro

“…Antibodies are a critical part of the immune system, having the function of directly neutralising or tagging undesirable objects (the antigens) for future…”
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How to transfer algorithmic reasoning knowledge to learn new algorithms? by Xhonneux, Louis-Pascal A. C, Deac, Andreea, Velickovic, Petar, Tang, Jian

“…Learning to execute algorithms is a fundamental problem that has been widely studied. Prior work~\cite{veli19neural} has shown that to enable systematic…”
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Neural Algorithmic Reasoners are Implicit Planners by Deac, Andreea, Veličković, Petar, Milinković, Ognjen, Bacon, Pierre-Luc, Tang, Jian, Nikolić, Mladen

“…Implicit planning has emerged as an elegant technique for combining learned models of the world with end-to-end model-free reinforcement learning. We study the…”
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XLVIN: eXecuted Latent Value Iteration Nets by Deac, Andreea, Veličković, Petar, Milinković, Ognjen, Bacon, Pierre-Luc, Tang, Jian, Nikolić, Mladen

“…Value Iteration Networks (VINs) have emerged as a popular method to incorporate planning algorithms within deep reinforcement learning, enabling performance…”
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A Generalist Neural Algorithmic Learner by Ibarz, Borja, Kurin, Vitaly, Papamakarios, George, Nikiforou, Kyriacos, Bennani, Mehdi, Csordás, Róbert, Dudzik, Andrew, Bošnjak, Matko, Vitvitskyi, Alex, Rubanova, Yulia, Deac, Andreea, Bevilacqua, Beatrice, Ganin, Yaroslav, Blundell, Charles, Veličković, Petar

“…The cornerstone of neural algorithmic reasoning is the ability to solve algorithmic tasks, especially in a way that generalises out of distribution. While…”
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Large-scale graph representation learning with very deep GNNs and self-supervision by Addanki, Ravichandra, Battaglia, Peter W, Budden, David, Deac, Andreea, Godwin, Jonathan, Keck, Thomas, Li, Wai Lok Sibon, Sanchez-Gonzalez, Alvaro, Stott, Jacklynn, Thakoor, Shantanu, Veličković, Petar

“…Effectively and efficiently deploying graph neural networks (GNNs) at scale remains one of the most challenging aspects of graph representation learning. Many…”
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Drug-Drug Adverse Effect Prediction with Graph Co-Attention by Deac, Andreea, Huang, Yu-Hsiang, Veličković, Petar, Liò, Pietro, Tang, Jian

“…Complex or co-existing diseases are commonly treated using drug combinations, which can lead to higher risk of adverse side effects. The detection of…”
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