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Embedding Learning

3,751 papers

Papers per year

Papers

Node Embeddings and Exact Low-Rank Representations of Complex Networks NIPS 2020
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction NIPS 2020
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering NIPS 2020
Inductive Quantum Embedding NIPS 2020
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models NIPS 2020
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies NIPS 2020
Deep Metric Learning with Spherical Embedding NIPS 2020
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings NIPS 2020
Graph Information Bottleneck NIPS 2020
Curvature Regularization to Prevent Distortion in Graph Embedding NIPS 2020
User-Dependent Neural Sequence Models for Continuous-Time Event Data NIPS 2020
Set2Graph: Learning Graphs From Sets NIPS 2020
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation CORL 2020
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs CORL 2020
Deep Match to Rank Model for Personalized Click-Through Rate Prediction AAAI 2020
Multi-Feature Discrete Collaborative Filtering for Fast Cold-Start Recommendation AAAI 2020
Learning to Match on Graph for Fashion Compatibility Modeling AAAI 2020
Multi-Channel Reverse Dictionary Model AAAI 2020
Learning Geo-Contextual Embeddings for Commuting Flow Prediction AAAI 2020
Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments AAAI 2020
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context AAAI 2020
Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding AAAI 2020
ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion AAAI 2020
Path Ranking with Attention to Type Hierarchies AAAI 2020
Rule-Guided Compositional Representation Learning on Knowledge Graphs AAAI 2020