Philip S Yu
13 papers · 2017–2024 · 4 venues · across top CS/AI venues
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π£ Hot Topic Early Bird π Conference Polyglot Β· Bronze π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (32)
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Research topics
Machine Learning
(12)
Deep Learning
(10)
Core Methods
(10)
Architectures
(9)
Learning Types Β· Deep Learning
(7)
Learning Types Β· Machine Learning
(5)
Artificial Intelligence
(2)
Application Areas
(2)
Core AI
(2)
Optimization & Theory
(2)
Computer Science
(1)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Applications
(1)
Keywords
graph neural network
(8)
self-supervised learning
(3)
node classification
(3)
representation learning
(3)
contrastive learning
(2)
graph representation learning
(2)
recurrent neural network
(2)
video prediction
(2)
conformal prediction
(1)
graph classification
(1)
multi-task learning
(1)
uncertainty quantification
(1)
anomaly detection
(1)
transfer learning
(1)
benchmark evaluation
(1)
deep learning
(1)
community detection
(1)
variational inference
(1)
language understanding
(1)
text understanding
(1)
Papers
GC-Bench: An Open and Unified Benchmark for Graph Condensation
NeurIPS 2024
Spiking Graph Neural Network on Riemannian Manifolds
NeurIPS 2024
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models
NeurIPS 2024
Equal Opportunity of Coverage in Fair Regression
NeurIPS 2023
A Self-Supervised Mixed-Curvature Graph Neural Network
AAAI 2022
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
NeurIPS 2022
Graph Structure Learning with Variational Information Bottleneck
AAAI 2022
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination
NeurIPS 2022
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
NeurIPS 2021
Deep Learning for Community Detection: Progress, Challenges and Opportunities
IJCAI 2020
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
ICML 2018
Learning Multiple Tasks with Multilinear Relationship Networks
NeurIPS 2017
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
NeurIPS 2017