Yusu Wang
34 papers · 2011–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (9) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (15) π Academic Marathon (14)
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Renaissance Researcher
(7)
π§
Keyword Pioneer
π
Cross-Pollinator
(10)
π¬
Deep Specialist
(11)
π§¬
Topic Evolution
π
Keyword Champion
π
Grand Slam
π₯
Mega-Team
(22)
π±
Topic Pioneer
π
Century Club
(34)
ποΈ
Keyword Collector
(56)
β‘
Prolific Year
(8)
π₯
Unstoppable
(12)
π
Trend Setter
Conferences
ICML (11)
NIPS (7)
AISTATS (5)
ALT (3)
AAAI (2)
COLT (2)
ICLR (2)
IJCAI (1)
JMLR (1)
Top co-authors
Keywords
graph neural network
(8)
persistent homology
(6)
topological data analysis
(3)
topological feature
(3)
message passing
(3)
kernel methods
(3)
graph transformer
(2)
stochastic blockmodel
(2)
node classification
(2)
dimensionality reduction
(2)
manifold learning
(2)
representation learning
(2)
markov chain
(2)
approximation algorithm
(2)
weisfeiler-lehman test
(2)
graph representation learning
(2)
combinatorial optimization
(2)
universal approximation
(2)
feature learning
(2)
metric learning
(2)
Papers
Enhancing Graph Representation Learning with Localized Topological Features
JMLR 2025
Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers
ICML 2025
De-coupled NeuroGF for Shortest Path Distance Approximations on Large Terrain Graphs
ICML 2025
Universal Representation of Permutation-Invariant Functions on Vectors and Tensors
ALT 2024
NN-Steiner: A Mixed Neural-Algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem
AAAI 2024
Learning Ultrametric Trees for Optimal Transport Regression
AAAI 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers
AISTATS 2024
DE-HNN: An effective neural model for Circuit Netlist representation
AISTATS 2024
Distances for Markov Chains, and Their Differentiation
ALT 2024
Comparing Graph Transformers via Positional Encodings
ICML 2024
Position: Topological Deep Learning is the New Frontier for Relational Learning
ICML 2024
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
NIPS 2023
The Numerical Stability of Hyperbolic Representation Learning
ICML 2023
Implicit Graphon Neural Representation
AISTATS 2023
On the Connection Between MPNN and Graph Transformer
ICML 2023
Understanding Oversquashing in GNNs through the Lens of Effective Resistance
ICML 2023
Convergence of Invariant Graph Networks
ICML 2022
Neural Approximation of Graph Topological Features
NIPS 2022
Generative Coarse-Graining of Molecular Conformations
ICML 2022
Weisfeiler-Lehman Meets Gromov-Wasserstein
ICML 2022
Topology-Aware Segmentation Using Discrete Morse Theory
ICLR 2021
NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs
NIPS 2021
Graph Coarsening with Neural Networks
ICLR 2021
Persistence Enhanced Graph Neural Network
AISTATS 2020
Learning metrics for persistence-based summaries and applications for graph classification
NIPS 2019
Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction
IJCAI 2019
A Topological Regularizer for Classifiers via Persistent Homology
AISTATS 2019
Unperturbed: spectral analysis beyond Davis-Kahan
ALT 2018
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
ICML 2017
Graphons, mergeons, and so on!
NIPS 2016
Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering
COLT 2015
Learning with Fredholm Kernels
NIPS 2014
Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries
COLT 2012
Data Skeletonization via Reeb Graphs
NIPS 2011