Philip S Yu
13 papers · 2017–2024 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Academic Marathon (7) π Conference Polyglot (4) π Renaissance Researcher (7) πΊοΈ Taxonomy Completionist (32)
π
Interdisciplinary Bridge
π
Academic Marathon
(7)
π§
Keyword Pioneer
π§¬
Topic Evolution
π
Trend Setter
π₯
Unstoppable
(5)
π
Century Club
(13)
ποΈ
Keyword Collector
(65)
Conferences
NIPS (9)
AAAI (2)
ICML (1)
IJCAI (1)
Top co-authors
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
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models
NIPS 2024
Spiking Graph Neural Network on Riemannian Manifolds
NIPS 2024
GC-Bench: An Open and Unified Benchmark for Graph Condensation
NIPS 2024
Equal Opportunity of Coverage in Fair Regression
NIPS 2023
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
NIPS 2022
Graph Structure Learning with Variational Information Bottleneck
AAAI 2022
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination
NIPS 2022
A Self-Supervised Mixed-Curvature Graph Neural Network
AAAI 2022
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
NIPS 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
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
NIPS 2017
Learning Multiple Tasks with Multilinear Relationship Networks
NIPS 2017