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Representation Learning

4,516 papers

Papers per year

Papers

Independence Promoted Graph Disentangled Networks AAAI 2020
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk AAAI 2020
Structured Sparsification of Gated Recurrent Neural Networks AAAI 2020
The HSIC Bottleneck: Deep Learning without Back-Propagation AAAI 2020
Multi-Zone Unit for Recurrent Neural Networks AAAI 2020
Deep Embedded Non-Redundant Clustering AAAI 2020
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs AAAI 2020
Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification AAAI 2020
Temporal Network Embedding with High-Order Nonlinear Information AAAI 2020
Actionable Ethics through Neural Learning AAAI 2020
Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020
Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution AAAI 2020
Deep Message Passing on Sets AAAI 2020
Hierarchically Clustered Representation Learning AAAI 2020
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers AAAI 2020
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip AAAI 2020
New Interpretations of Normalization Methods in Deep Learning AAAI 2020
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values AAAI 2020
Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance AAAI 2020
Vector Quantization-Based Regularization for Autoencoders AAAI 2020
Learning Feature Interactions with Lorentzian Factorization Machine AAAI 2020
Gromov-Wasserstein Factorization Models for Graph Clustering AAAI 2020
Shared Generative Latent Representation Learning for Multi-View Clustering AAAI 2020
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence AAAI 2020
PIQA: Reasoning about Physical Commonsense in Natural Language AAAI 2020