Gaoyuan Zhang
9 papers · 2020–2024 · 6 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
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Conference Polyglot · Silver
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Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(20)
🏆
Grand Slam
❓
The Questioner
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Research topics
Machine Learning
(7)
Learning Types · Machine Learning
(7)
Artificial Intelligence
(4)
Deep Learning
(4)
Core AI
(4)
Learning Types · Deep Learning
(2)
Models
(2)
Computer Vision
(1)
Application Areas
(1)
Core Methods
(1)
Generation
(1)
Optimization & Theory · Deep Learning
(1)
Optimization & Theory · Machine Learning
(1)
Techniques
(1)
Keywords
adversarial robustness
(4)
robust classification
(2)
adversarial attack
(2)
image generation
(1)
self-supervised learning
(1)
code generation
(1)
distributed learning
(1)
adversarial training
(1)
text-to-image generation
(1)
machine unlearning
(1)
feature representation
(1)
diffusion model
(1)
deep neural network
(1)
gradient compression
(1)
generative adversarial network
(1)
adversarial prompt
(1)
class-conditional generation
(1)
artistic style
(1)
first-order optimization
(1)
model interpretation
(1)
Papers
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
NeurIPS 2024
An Adversarial Framework for Generating Unseen Images by Activation Maximization
AAAI 2022
Distributed adversarial training to robustify deep neural networks at scale
UAI 2022
Fast Training of Provably Robust Neural Networks by SingleProp
AAAI 2021
Generating Adversarial Computer Programs using Optimized Obfuscations
ICLR 2021
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
NeurIPS 2021
Adversarial T-shirt! Evading Person Detectors in A Physical World
ECCV 2020
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
ECCV 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification
ICML 2020