← Core AI
Artificial Intelligence › Core AI ›

AI Safety

2972 directly classified papers

Papers per year

Papers

Topological Detection of Trojaned Neural Networks NIPS 2021
Backdoor Attack with Imperceptible Input and Latent Modification NIPS 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds NIPS 2021
Morié Attack (MA): A New Potential Risk of Screen Photos NIPS 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses NIPS 2021
Neural Architecture Dilation for Adversarial Robustness NIPS 2021
Adversarial Robustness with Semi-Infinite Constrained Learning NIPS 2021
Disrupting Deep Uncertainty Estimation Without Harming Accuracy NIPS 2021
Misspecification in Prediction Problems and Robustness via Improper Learning AISTATS 2021
Provably Safe and Efficient Motion Planning with Uncertain Human Dynamics RSS 2021
Robustness Certification for Point Cloud Models ICCV 2021
Learnable Boundary Guided Adversarial Training ICCV 2021
Towards Robustness of Deep Neural Networks via Regularization ICCV 2021
Infinite Time Horizon Safety of Bayesian Neural Networks NIPS 2021
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning NIPS 2021
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs NIPS 2021
Counterexample Guided RL Policy Refinement Using Bayesian Optimization NIPS 2021
Optimal Policies Tend To Seek Power NIPS 2021
Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations NIPS 2021
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? NIPS 2021
Robust learning under clean-label attack COLT 2021
Adversarially Robust Learning with Unknown Perturbation Sets COLT 2021
Model-free Safe Control for Zero-Violation Reinforcement Learning CORL 2021
Auditing Robot Learning for Safety and Compliance during Deployment CORL 2021
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee NIPS 2021