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06/20/2023
A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design
Structure-based drug design (SBDD), which utilizes the three-dimensional...
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05/22/2023
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design
Generating molecules with high binding affinities to target proteins (a....
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03/13/2023
Backdoor Defense via Deconfounded Representation Learning
Deep neural networks (DNNs) are recently shown to be vulnerable to backd...
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12/11/2022
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense
Federated recommendation (FedRec) can train personalized recommenders wi...
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10/20/2022
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information
Federated learning is vulnerable to poisoning attacks in which malicious...
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10/08/2022
Hierarchical Graph Transformer with Adaptive Node Sampling
The Transformer architecture has achieved remarkable success in a number...
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10/02/2022
FLCert: Provably Secure Federated Learning against Poisoning Attacks
Due to its distributed nature, federated learning is vulnerable to poiso...
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09/16/2022
Model Inversion Attacks against Graph Neural Networks
Many data mining tasks rely on graphs to model relational structures amo...
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07/19/2022
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients
Federated learning (FL) is vulnerable to model poisoning attacks, in whi...
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12/02/2021
ProtGNN: Towards Self-Explaining Graph Neural Networks
Despite the recent progress in Graph Neural Networks (GNNs), it remains ...
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10/03/2021
Motif-based Graph Self-Supervised Learning forMolecular Property Prediction
Predicting molecular properties with data-driven methods has drawn much ...
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06/05/2021
GraphMI: Extracting Private Graph Data from Graph Neural Networks
As machine learning becomes more widely used for critical applications, ...
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06/19/2020
