A New Perspective On AI Safety Through Control Theory Methodologies | Paper Citation Record

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This paper cites Object Classification Using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment,.

A New Perspective On AI Safety Through Control Theory Methodologies Object Classification Using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment,

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This paper cites Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective,.

A New Perspective On AI Safety Through Control Theory Methodologies Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective,

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This paper cites A comprehensive survey of clustering algorithms: State-of-the-art machine learning ap- plications, taxonomy, challenges, and future research prospects,.

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This paper cites An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools,.

A New Perspective On AI Safety Through Control Theory Methodologies An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools,

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This paper cites A Comprehensive Survey on Transfer Learning,.

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A New Perspective On AI Safety Through Control Theory Methodologies Unsupervised Learning,

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A New Perspective On AI Safety Through Control Theory Methodologies Unresolved cited work

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This paper cites Girod, R.

A New Perspective On AI Safety Through Control Theory Methodologies Girod, R

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This paper cites The rise of artificial intelligence in healthcare applications,.

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This paper cites Developing artificial neural networks for safety critical systems,.

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This paper cites Challenges in Using Neural Networks in Safety-Critical Applications,.

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This paper cites Artificial Intelligence in Education: A Review,.

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This paper cites Matching Networks for One Shot Learning,.

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This paper cites Safety Assurance of Artificial Intelligence-Based Systems: A Systematic Literature Review on the State of the Art and Guidelines for Future Work,.

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This paper cites The Role of Explainability in Assuring Safety of Machine Learning in Healthcare,.

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This paper cites DLOAM: Real-time and Robust LiDAR SLAM System Based on CNN in Dynamic Urban Environments,.

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This paper cites Lunze,Regelungstechnik 1: Systemtheoretische Grundlagen, Analyse und Entwurf einschleifiger Regelungen.

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This paper cites Data-Driven Model Predictive Control With Stability and Robustness Guarantees,.

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This paper cites Training Robust Neural Networks Using Lipschitz Bounds,.

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This paper cites Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL,.

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This paper cites Online Reinforcement Learning in Stochastic Games,.

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This paper cites Robustness and Adaptability of Reinforcement Learning-Based Cooperative Autonomous Driving in Mixed-Autonomy Traffic,.

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Observation f50eb15e-ba8a-4a0e-a1e9-930e165fd329 · outbound

This paper cites Learning-Based Safe Control for Robot and Autonomous Vehicle Using Efficient Safety Certificate,.

A New Perspective On AI Safety Through Control Theory Methodologies Learning-Based Safe Control for Robot and Autonomous Vehicle Using Efficient Safety Certificate,

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A New Perspective On AI Safety Through Control Theory Methodologies Data-Driven Safety Filters: Hamilton-Jacobi Reachability, Control Barrier Functions, and Predictive Methods for Uncertain Systems,

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Observation 6e42b651-e66f-4e9e-b96b-9bc2123df349 · outbound

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A New Perspective On AI Safety Through Control Theory Methodologies Predictive safety filter using system level synthesis,

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This paper cites Model Predictive Control,.

A New Perspective On AI Safety Through Control Theory Methodologies Model Predictive Control,

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This paper cites From model-based control to data-driven control: Survey, classification and perspective,.

A New Perspective On AI Safety Through Control Theory Methodologies From model-based control to data-driven control: Survey, classification and perspective,

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A New Perspective On AI Safety Through Control Theory Methodologies An Overview of Dynamic-Linearization- Based Data-Driven Control and Applications,

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A New Perspective On AI Safety Through Control Theory Methodologies Data-driven control: A behavioral approach,

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A New Perspective On AI Safety Through Control Theory Methodologies Formulas for Data-Driven Control: Stabiliza- tion, Optimality, and Robustness,

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A New Perspective On AI Safety Through Control Theory Methodologies Data-driven mpc for quadrotors,

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A New Perspective On AI Safety Through Control Theory Methodologies Behavioral systems theory in data-driven analysis, signal processing, and control,

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A New Perspective On AI Safety Through Control Theory Methodologies Learning model predictive control for iterative tasks. a data-driven control framework,

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A New Perspective On AI Safety Through Control Theory Methodologies Bridging Direct and Indirect Data-Driven Control Formulations via Regularizations and Relaxations,

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A New Perspective On AI Safety Through Control Theory Methodologies Adaptive Observer Based Data-Driven Control for Nonlinear Discrete-Time Processes,

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A New Perspective On AI Safety Through Control Theory Methodologies A Behavioral Approach to Data-Driven Control With Noisy Input–Output Data,

Reference 76

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A New Perspective On AI Safety Through Control Theory Methodologies Flight Test Validation of a Safety-Critical Neural Network Based Longitudinal Controller for a Fixed-Wing UAS,

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Observation bb002ed7-dab1-4f1d-8ef1-f542e9d97c54 · outbound

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A New Perspective On AI Safety Through Control Theory Methodologies On Causal and Anticausal Learning

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A New Perspective On AI Safety Through Control Theory Methodologies Covariate Shift Adap- tation by Importance Weighted Cross Validation,

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A New Perspective On AI Safety Through Control Theory Methodologies Domain Adaptation under Target and Conditional Shift,

Reference 80

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A New Perspective On AI Safety Through Control Theory Methodologies Reliable Decision Support using Counter- factual Models,

Reference 81

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This paper cites Pearl,Causality.

A New Perspective On AI Safety Through Control Theory Methodologies Pearl,Causality

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A New Perspective On AI Safety Through Control Theory Methodologies Towards a multi-agent vision-language system for zero-shot novel hazardous object detection for autonomous driving safety,

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A New Perspective On AI Safety Through Control Theory Methodologies Perception without vision for trajectory prediction: Ego vehicle dynamics as scene representation for efficient active learning in autonomous driving,

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A New Perspective On AI Safety Through Control Theory Methodologies Generalizing from a Few Examples: A Survey on Few-shot Learning,

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A New Perspective On AI Safety Through Control Theory Methodologies Language-driven active learning for diverse open-set 3d object detection,

Reference 86

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A New Perspective On AI Safety Through Control Theory Methodologies Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

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A New Perspective On AI Safety Through Control Theory Methodologies Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks,

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A New Perspective On AI Safety Through Control Theory Methodologies Data-driven distributionally ro- bust optimization using the Wasserstein metric: performance guarantees and tractable reformulations,

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A New Perspective On AI Safety Through Control Theory Methodologies Certifying Some Distributional Robustness with Principled Adversarial Training

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A New Perspective On AI Safety Through Control Theory Methodologies Distributionally Robust Optimization: A Review

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This paper cites From development to deployment: dataset shift, causality, and shift-stable models in health AI,.

A New Perspective On AI Safety Through Control Theory Methodologies From development to deployment: dataset shift, causality, and shift-stable models in health AI,

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A New Perspective On AI Safety Through Control Theory Methodologies Evaluating model robustness and stability to dataset shift,

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Observation f1ded096-8dd8-4c59-a2e2-7dcd8fa6953e · outbound

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A New Perspective On AI Safety Through Control Theory Methodologies Concrete Problems in AI Safety

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A New Perspective On AI Safety Through Control Theory Methodologies Evaluation of CNN-Based Ap- proaches to Adverse Weather Image Classification for Autonomous Driving Systems,

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A New Perspective On AI Safety Through Control Theory Methodologies Causal Modeling for Training and Evaluating Dataset Shift-Stable Machine Learning Models in Healthcare,

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Observation 1d9c8b62-1471-4187-81c3-0da5e7a61a5e · outbound

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A New Perspective On AI Safety Through Control Theory Methodologies Learning repre- sentations by back-propagating errors,

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A New Perspective On AI Safety Through Control Theory Methodologies A Path Towards Autonomous Machine Intelligence Version 0.9. 2, 2022-06-27,

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