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CorrectAndSmooth
CorrectAndSmooth Public[ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)
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Non-Homophily-Large-Scale
Non-Homophily-Large-Scale Public[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
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Neural-Manifold-Ordinary-Differential-Equations
Neural-Manifold-Ordinary-Differential-Equations Public[NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
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Non-Homophily-Benchmarks
Non-Homophily-Benchmarks Public[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
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Intermediate-Level-Attack
Intermediate-Level-Attack Public[ICCV 2019] Enhancing Adversarial Example Transferability with an Intermediate Level Attack (https://arxiv.org/abs/1907.10823)
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Differentiable-Frechet-Mean
Differentiable-Frechet-Mean Public[ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
Repositories
- Riemannian-Residual-Neural-Networks Public
[NeurIPS 2023] Riemannian Residual Neural Networks (https://arxiv.org/abs/2006.10254)
CUAI/Riemannian-Residual-Neural-Networks’s past year of commit activity - Neural-Manifold-Ordinary-Differential-Equations Public
[NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
CUAI/Neural-Manifold-Ordinary-Differential-Equations’s past year of commit activity - Non-Homophily-Large-Scale Public
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
CUAI/Non-Homophily-Large-Scale’s past year of commit activity - Equivariant-Manifold-Flows Public
[NeurIPS 2021] Equivariant Manifold Flows (https://arxiv.org/abs/2107.08596)
CUAI/Equivariant-Manifold-Flows’s past year of commit activity - Non-Homophily-Benchmarks Public
[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
CUAI/Non-Homophily-Benchmarks’s past year of commit activity - Differentiable-Frechet-Mean Public
[ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
CUAI/Differentiable-Frechet-Mean’s past year of commit activity - CorrectAndSmooth Public
[ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)
CUAI/CorrectAndSmooth’s past year of commit activity