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Poster
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Tue 17:00
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From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou · Xiyuan Wang · Muhan Zhang
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Workshop
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Label Noise: Correcting a Correction Loss
William Toner · Amos Storkey
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Workshop
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Establishing a Benchmark for Adversarial Robustness of Compressed Deep Learning Models after Pruning
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Workshop
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Label Noise: Correcting a Correction Loss
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Workshop
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Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Lingam · Mohammad Sadegh Akhondzadeh · Aleksandar Bojchevski
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Workshop
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How Can Neuroscience Help Us Build More Robust Deep Neural Networks?
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Workshop
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Adaptive Certified Training: Towards Better Accuracy-Robustness Tradeoffs
Zhakshylyk Nurlanov · Frank R Schmidt · Florian Bernard
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Poster
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Tue 14:00
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Graph Neural Networks with Learnable and Optimal Polynomial Bases
Yuhe Guo · Zhewei Wei
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Poster
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Wed 14:00
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Towards Understanding Generalization of Graph Neural Networks
Huayi Tang · Yong Liu
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Workshop
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Benchmarking Adversarial Robustness of Compressed Deep Learning Models
Brijesh Vora · Kartik Patwari · Syed Mahbub Hafiz · Zubair Shafiq · Chen-Nee Chuah
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Workshop
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Anomaly Detection in Networks via Score-Based Generative Models
Dmitrii Gavrilev · Evgeny Burnaev
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Workshop
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Fri 12:10
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Prof. Marta Kwiatkowska (Oxford): Robustness Guarantees for Bayesian Neural Networks
Marta Kwiatkowska
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