Mao, Yuhao

1. Understanding Certified Training with Interval Bound Propagation
   2023/06/17 by Yuhao Mao, Mark Niklas Müller, Mao, Yuhao +5 · 4 citations
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
2. Repeat-Aware Neighbor Sampling for Dynamic Graph Learning
   2024/05/24 by Zou, Tao, Mao, Yuhao, Ye, Junchen +1 · 4 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Social and Information Networks (cs.SI)
3. CTBENCH: A Library and Benchmark for Certified Training
   2024/06/07 by Yuhao Mao, Stefan Balauca, Mao, Yuhao +3 · 4 citations
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
4. Expressivity of ReLU-Networks under Convex Relaxations
   2023/11/07 by Maximilian Baader, Baader, Maximilian, Mark Niklas Müller +5 · 2 citations
   Computer Science · Engineering · #Adversarial Robustness in Machine Learning #Advanced Memory and Neural Computing #Neural Networks and Applications
5. TAPS: Connecting Certified and Adversarial Training
   2023/05/08 by Yuhao Mao, Mark Niklas Müller, Mao, Yuhao +5 · 1 citation
   Computer Science · #Adversarial Robustness in Machine Learning #Advanced Neural Network Applications #Anomaly Detection Techniques and Applications
6. Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings
   2022/04/07 by Yuhao Mao, Chong Fu, Mao, Yuhao +17 · 1 citation
   Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Computers and Society (cs.CY) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Radiation Detection and Scintillator Technologies
7. Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations
   2024/03/11 by Balauca, Stefan, Müller, Mark Niklas, Mao, Yuhao +3 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG)