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Worst-case Satisfaction of STL Specifications Using Feedforward Neural Network Controllers
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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An introduction to the use of neural networks in control systems
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Safe At Any Speed: A Simulation-Based Test Harness for Autonomous Vehicles
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Compositional Falsification of Cyber-Physical Systems with Machine Learning Components
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Classification and Coverage-Based Falsification for Embedded Control Systems
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Lectures on Runtime Verification. Introductory and Advanced Topics
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Semantic Adversarial Deep Learning
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Monitoring Temporal Properties of Continuous Signals
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Evaluating the CMA Evolution Strategy on Multimodal Test Functions
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Applications of Neural Networks in High Assurance Systems
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Breach, A Toolbox for Verification and Parameter Synthesis of Hybrid Systems
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Robust Satisfaction of Temporal Logic over Real-Valued Signals
inferredcites →https://doi.org/10.1007/978-3-642-19835-9_21openalex-snapshot
S-TaLiRo: A Tool for Temporal Logic Falsification for Hybrid Systems
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SpaceEx: Scalable Verification of Hybrid Systems
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Flow*: An Analyzer for Non-linear Hybrid Systems
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Formal Techniques, Modelling and Analysis of Timed and Fault-Tolerant Systems
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Specifying real-time properties with metric temporal logic
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Multilayer feedforward networks are universal approximators
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Constrained Optimization and Lagrange Multiplier Methods
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Generating Dominant Strategies for Continuous Two-Player Zero-Sum Games
inferredcites →https://doi.org/10.1016/j.ifacol.2018.08.018openalex-snapshot
Falsification of Temporal Logic Requirements Using Gradient Based Local Search in Space and Time
inferredcites →https://doi.org/10.1016/j.ifacol.2018.08.026openalex-snapshot
Learning and Verification of Feedback Control Systems using Feedforward Neural Networks
inferredcites →https://doi.org/10.1016/j.neucom.2017.08.017openalex-snapshot
Neural network based optimization approach for energy demand prediction in smart grid
inferredcites →https://doi.org/10.1016/j.tcs.2009.06.021openalex-snapshot
Robustness of temporal logic specifications for continuous-time signals
inferredcites →https://doi.org/10.1109/acc.2008.4587155openalex-snapshot
Neural network solution for forward kinematics problem of HEXA parallel robot
inferredcites →https://doi.org/10.1109/ccta.2017.8062628openalex-snapshot
Smooth operator: Control using the smooth robustness of temporal logic
inferredcites →https://doi.org/10.1109/cdc.2014.7039363openalex-snapshot
Model predictive control with signal temporal logic specifications
inferredcites →https://doi.org/10.1109/cdc.2017.8264430openalex-snapshot
Design of deep neural networks as add-on blocks for improving impromptu trajectory tracking
inferredcites →https://doi.org/10.1109/dasc.2016.7778091openalex-snapshot
Policy compression for aircraft collision avoidance systems
inferredcites →https://doi.org/10.1109/iccps.2018.00026openalex-snapshot
Fly-by-Logic: Control of Multi-Drone Fleets with Temporal Logic Objectives
inferredcites →https://doi.org/10.1109/icra.2016.7487175openalex-snapshot
Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search
inferredcites →https://doi.org/10.1109/icra.2017.7989202openalex-snapshot
Information theoretic MPC for model-based reinforcement learning
inferredcites →https://doi.org/10.1109/icra.2018.8460811openalex-snapshot
Learning-Based Model Predictive Control Under Signal Temporal Logic Specifications
inferredcites →https://doi.org/10.1109/iros.2017.8206235openalex-snapshot
Sampling-based synthesis of maximally-satisfying controllers for temporal logic specifications
inferredcites →https://doi.org/10.1109/ivs.2018.8500421openalex-snapshot
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components
inferredcites →https://doi.org/10.1109/lcsys.2018.2843682openalex-snapshot
Learning an Approximate Model Predictive Controller With Guarantees
inferredcites →https://doi.org/10.1109/tcst.2010.2054092openalex-snapshot
Nonlinear Model Predictive Control With Neural Network Optimization for Autonomous Autorotation of Small Unmanned Helicopters
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/2728606.2728628openalex-snapshot
Reactive synthesis from signal temporal logic specifications
inferredcites →https://doi.org/10.1145/3126510openalex-snapshot
Timestamp Temporal Logic (TTL) for Testing the Timing of Cyber-Physical Systems
inferredcites →https://doi.org/10.1145/3302504.3311807openalex-snapshot
Reachability analysis for neural feedback systems using regressive polynomial rule inference
inferredcites →https://doi.org/10.1145/3302504.3311814openalex-snapshot
Gray-box adversarial testing for control systems with machine learning components
inferredcites →https://doi.org/10.1145/3302509.3311053openalex-snapshot
Reduced variance deep reinforcement learning with temporal logic specifications
inferredcites →https://doi.org/10.1162/106365601750190398openalex-snapshot
Completely Derandomized Self-Adaptation in Evolution Strategies
inferredcites →https://doi.org/10.1609/icaps.v29i1.3555openalex-snapshot
Trajectory Tracking Control for Robotic Vehicles Using Counterexample Guided Training of Neural Networks
inferredcites →https://doi.org/10.18419/opus-9722openalex-snapshot
Learning an approximate model predictive controller with guarantees
inferredcites →https://doi.org/10.23919/acc.2018.8431181openalex-snapshot
A Policy Search Method For Temporal Logic Specified Reinforcement Learning Tasks
inferredcites →https://doi.org/10.24963/ijcai.2018/286openalex-snapshot
Counterexample-Guided Data Augmentation
inferredcites →https://doi.org/10.48550/arxiv.1211.5063openalex-snapshot
On the difficulty of training Recurrent Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1810.01989openalex-snapshot
Verification for Machine Learning, Autonomy, and Neural Networks Survey
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Multilayer feedforward networks are universal approximators
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-32079-9_3openalex-snapshot
Robustness of Specifications and Its Applications to Falsification, Parameter Mining, and Runtime Monitoring with S-TaLiRo
inferred← citeshttps://doi.org/10.1007/978-3-030-66723-8_26openalex-snapshot
Back-Propagation Through Signal Temporal Logic Specifications: Infusing Logical Structure into Gradient-Based Methods
inferred← citeshttps://doi.org/10.1007/s11042-023-14634-4openalex-snapshot
Multilayer extreme learning machine: a systematic review
inferred← citeshttps://doi.org/10.1016/j.automatica.2022.110184openalex-snapshot
Formal synthesis of closed-form sampled-data controllers for nonlinear continuous-time systems under STL specifications
inferred← citeshttps://doi.org/10.1016/j.ifacol.2024.07.445openalex-snapshot
LB4TL: A Smooth Semantics for Temporal Logic to Train Neural Feedback Controllers
inferred← citeshttps://doi.org/10.1109/cdc45484.2021.9682921openalex-snapshot
Neural Network-based Control for Multi-Agent Systems from Spatio-Temporal Specifications
inferred← citeshttps://doi.org/10.1109/cdc45484.2021.9683756openalex-snapshot
Risk-Bounded Control with Kalman Filtering and Stochastic Barrier Functions
inferred← citeshttps://doi.org/10.1109/cdc49753.2023.10383831openalex-snapshot
Counter-Example Guided Imitation Learning of Feedback Controllers from Temporal Logic Specifications
inferred← citeshttps://doi.org/10.1109/itsc45102.2020.9294485openalex-snapshot
Training Neural Network Controllers Using Control Barrier Functions in the Presence of Disturbances
inferred← citeshttps://doi.org/10.1109/lcsys.2021.3049917openalex-snapshot
Recurrent Neural Network Controllers for Signal Temporal Logic Specifications Subject to Safety Constraints
inferred← citeshttps://doi.org/10.1109/lcsys.2025.3579761openalex-snapshot
Approximation-Free Control for Signal Temporal Logic Specifications Using Spatiotemporal Tubes
inferred← citeshttps://doi.org/10.1109/tac.2022.3195470openalex-snapshot
Receding Horizon Control With Online Barrier Function Design Under Signal Temporal Logic Specifications
inferred← citeshttps://doi.org/10.1109/tac.2025.3538747openalex-snapshot
Quantifying the Satisfaction of Spatio-Temporal Logic Specifications for Multiagent Control
inferred← citeshttps://doi.org/10.1109/tcad.2020.3012804openalex-snapshot
Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices
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TKD: Temporal Knowledge Distillation for Active Perception
inferred← citeshttps://doi.org/10.1145/3696112openalex-snapshot
Scaling Learning-based Policy Optimization for Temporal Logic Tasks by Controller Network Dropout
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Backpropagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods
inferred← citeshttps://doi.org/10.23919/acc50511.2021.9482725openalex-snapshot
Recurrent Neural Network Controllers for Signal Temporal Logic Specifications Subject to Safety Constraints
inferred← citeshttps://doi.org/10.23919/acc53348.2022.9867345openalex-snapshot
Semi-Supervised Trajectory-Feedback Controller Synthesis for Signal Temporal Logic Specifications
inferred← citeshttps://doi.org/10.23919/acc55779.2023.10156345openalex-snapshot
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives
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Recurrent Neural Network Controllers for Signal Temporal Logic Specifications Subject to Safety Constraints
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Local Repair of Neural Networks Using Optimization
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