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Applications
GANs / unsupervised
Network design
Foundations / Philosophy
RL
Graph networks
Optimization / training
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Kalman Normalization: Normalizing internal representations across network layers
MetaReg: towards Domain Generalization using meta-regularization
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(Direct) Feedback alignment
Geometric deep learning
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Convolutional Neural Networks on Surfaces via Seamless Toric Covers
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Deriving Neural Architectures from Sequence and Graph Kernels
CayleyNets: Graph convolutional neural networks with complex rational spectral filters
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence
Geometric matrix completion with recurrent multi-graph neural networks
Neural Message Passing for Quantum Chemistry
Deep Learning on Lie Groups for Skeleton-based Action Recognition
Other