Xiaowen Dong
27 papers · 2020–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (11) π Conference Polyglot (8)
πΊοΈ
Taxonomy Completionist
(11)
π§
Keyword Pioneer
π
Academic Marathon
(5)
π
Triple Crown
π
Century Club
(27)
π₯
Unstoppable
(6)
π
Trend Setter
ποΈ
Keyword Collector
(93)
β‘
Prolific Year
(5)
Conferences
ICLR (7)
NIPS (7)
ICML (5)
AISTATS (3)
UAI (2)
ACL (1)
COLING (1)
NAACL (1)
Top co-authors
Keywords
graph neural network
(7)
bayesian optimization
(4)
graph classification
(3)
gaussian process
(2)
strategic interaction
(2)
spectral graph wavelet
(2)
graph signal processing
(2)
network game
(2)
edge perturbation
(2)
black-box optimization
(2)
graph laplacian
(1)
hyperparameter optimization
(1)
graph learning
(1)
stance detection
(1)
manifold learning
(1)
sample efficiency
(1)
graph theory
(1)
nash equilibrium
(1)
temporal dynamics
(1)
instruction tuning
(1)
Papers
Separation Power of Equivariant Neural Networks
ICLR 2025
Training-Free Message Passing for Learning on Hypergraphs
ICLR 2025
Synthesizing Post-Training Data for LLMs through Multi-Agent Simulation
ACL 2025
On Measuring Long-Range Interactions in Graph Neural Networks
ICML 2025
Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes
AISTATS 2025
Bundle Neural Network for message diffusion on graphs
ICLR 2025
Neural Spacetimes for DAG Representation Learning
ICLR 2025
STEntConv: Predicting Disagreement between Reddit Users with Stance Detection and a Signed Graph Convolutional Network
COLING 2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations
ICLR 2024
Bayesian Optimization of Functions over Node Subsets in Graphs
NIPS 2024
Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
NIPS 2024
Graph classification Gaussian processes via spectral features
UAI 2023
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization
NIPS 2023
DRew: Dynamically Rewired Message Passing with Delay
ICML 2023
Structure-aware robustness certificates for graph classification
UAI 2023
Bayesian Optimisation of Functions on Graphs
NIPS 2023
Understanding over-squashing and bottlenecks on graphs via curvature
ICLR 2022
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
AISTATS 2022
Learning to Infer Structures of Network Games
ICML 2022
Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity
NAACL 2022
Beltrami Flow and Neural Diffusion on Graphs
NIPS 2021
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation
NIPS 2021
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
ICLR 2021
Interpretable Stability Bounds for Spectral Graph Filters
ICML 2021
Learning to Learn Graph Topologies
NIPS 2021
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis
AISTATS 2020
Learning Quadratic Games on Networks
ICML 2020