Summary of Neural Networks with Causal Graph Constraints: a New Approach For Treatment Effects Estimation, by Roger Pros et al.
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimationby Roger Pros,…
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimationby Roger Pros,…
Improved Generalization Bounds for Communication Efficient Federated Learningby Peyman Gholami, Hulya SeferogluFirst submitted to arxiv…
Hypergraph Self-supervised Learning with Sampling-efficient Signalsby Fan Li, Xiaoyang Wang, Dawei Cheng, Wenjie Zhang, Ying…
CORE: Data Augmentation for Link Prediction via Information Bottleneckby Kaiwen Dong, Zhichun Guo, Nitesh V.…
HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Predictionby Bin Liu, Siqi Wu, Jin Wang,…
AGHINT: Attribute-Guided Representation Learning on Heterogeneous Information Networks with Transformerby Jinhui Yuan, Shan Lu, Peibo…
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learningby Kyle Hsu, Jubayer Ibn Hamid, Kaylee…
RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networksby Haimin Zhang, Min XuFirst submitted to…
Neighbour-level Message Interaction Encoding for Improved Representation Learning on Graphsby Haimin Zhang, Min XuFirst submitted…
Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learningby Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao,…