Binghui Wang
20 papers · 2020–2025 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
🗺️ Taxonomy Completionist (28) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🏆
Grand Slam
👑
Triple Crown
⚡
Prolific Year · Productive
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
🌈
Renaissance Researcher
(6)
🗃️
Keyword Collector
(76)
Top co-authors
Research topics
Machine Learning
(16)
Artificial Intelligence
(11)
Core AI
(9)
Learning Types
(9)
Deep Learning
(8)
Application Areas
(8)
Architectures
(8)
Core Methods
(7)
Optimization & Theory
(6)
Learning Paradigms · Machine Learning
(3)
Computer Vision
(2)
Security & Privacy
(2)
Learning Paradigms · Artificial Intelligence
(2)
Privacy
(2)
Healthcare & Medicine
(1)
Keywords
graph neural network
(6)
adversarial attack
(4)
federated learning
(3)
privacy preservation
(3)
adversarial robustness
(3)
randomized smoothing
(3)
adversarial perturbation
(3)
certified robustness
(3)
representation learning
(3)
top-k prediction
(2)
attribute inference
(2)
graph classification
(2)
poisoning attack
(2)
evasion attack
(2)
black-box attack
(2)
certified defense
(2)
graph structure
(1)
adversarial learning
(1)
distributed learning
(1)
label noise handling
(1)
Papers
Breaking Data Silos in Parkinson’s Disease Diagnosis: An Adaptive Federated Learning Approach for Privacy-Preserving Facial Expression Analysis
AAAI 2025
Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations
CVPR 2025
Learning Robust and Privacy-Preserving Representations via Information Theory
AAAI 2025
Practicable Black-Box Evasion Attacks on Link Prediction in Dynamic Graphs—a Graph Sequential Embedding Method
AAAI 2025
Provably Robust Explainable Graph Neural Networks against Graph Perturbation Attacks
ICLR 2025
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning
NeurIPS 2024
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations
ICLR 2024
Graph Neural Network Causal Explanation via Neural Causal Models
ECCV 2024
Graph Neural Network Explanations are Fragile
ICML 2024
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks
AAAI 2024
IDGI: A Framework To Eliminate Explanation Noise From Integrated Gradients
CVPR 2023
Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation
WACV 2023
Turning Strengths Into Weaknesses: A Certified Robustness Inspired Attack Framework Against Graph Neural Networks
CVPR 2023
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations
ICLR 2022
Bandits for Structure Perturbation-Based Black-Box Attacks To Graph Neural Networks With Theoretical Guarantees
CVPR 2022
UniCR: Universally Approximated Certified Robustness via Randomized Smoothing
ECCV 2022
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks
AAAI 2021
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective
CVPR 2021
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
ICLR 2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
NeurIPS 2020