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Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming

https://doi.org/10.1109/tac.2020.3046193

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Towards a Geometric Understanding of Spatiotemporal Graph Convolution Networks

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Building Safe and Stable DNN Controllers using Deep Reinforcement Learning and Deep Imitation Learning

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An Approach to Build and Verify Stable Neural Network Controllers for Cyber Physical Systems with Non-Linear Dynamics

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Designing Deep Neural Net Controller for Quadrotor Attitude Stabilization

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Gradient Projection Differential Neural Solution for Quadratic Optimization with Quadratic Constraints: An ACP Perspective

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SoK: Certified Robustness for Deep Neural Networks

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Methodological Pathways for Safety and Risk Mitigation in Reduced Crew Aviation Operations

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Stability Analysis Using Quadratic Constraints for Systems With Neural Network Controllers

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Robust Output Regulation: Optimization-Based Synthesis and Event-Triggered Implementation

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Reliably-Stabilizing Piecewise-Affine Neural Network Controllers

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Stability Verification of Neural Network Controllers Using Mixed-Integer Programming

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Recurrent Equilibrium Networks: Flexible Dynamic Models With Guaranteed Stability and Robustness

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Structured, Reduced-Order $\mathcal{H}_{2}$-Conic Control

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Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loops

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Non-Euclidean Contraction Analysis of Continuous-Time Neural Networks

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Parameter-Dependent Robust Control Invariant Sets for LPV Systems With Bounded Parameter-Variation Rate

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Regional Stability Analysis of Discrete-Time Piecewise Affine Systems

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A Complete Set of Quadratic Constraints for Repeated ReLU and Generalizations

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Integrated Neural Fault-Tolerant Control Using LPV Sliding Mode Observer for Quadrotors

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Event-Triggered H∞ Tracking Control for Dynamic Artificial Neural Network Models With Time-Varying Delays

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Divide and Slide: Layer-Wise Refinement for Output Range Analysis of Deep Neural Networks

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POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems

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Adaptive Neural Stochastic Control With Lipschitz Constant Optimization

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Neural Schrödinger Bridge With Sinkhorn Losses: Application to Data-Driven Minimum Effort Control of Colloidal Self-Assembly

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Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective

inferred← citeshttps://doi.org/10.1109/tetci.2024.3358096openalex-snapshot

Generative Model Predictive Control: Approximating MPC Law With Generative Models

inferred← citeshttps://doi.org/10.1109/tie.2026.3675189openalex-snapshot

Data-Driven Control of PMSM via Neural Networks With Active Disturbance Learning

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Robust Longitudinal Control for Vehicular Platoons Using Deep Reinforcement Learning

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Reduced-Order Neural Network Synthesis With Robustness Guarantees

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Neural Observer With Lyapunov Stability Guarantee for Uncertain Nonlinear Systems

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A Distributed Neural Hybrid System Learning Framework in Modeling Complex Dynamical Systems

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A Unified Framework for Dynamics Modeling and Control Design Using Deep Learning With Side Information on Stabilizability

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Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

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Deep Learning for Continuous-Time Leader Synchronization in Graphical Games Using Sampling and Deep Neural Networks

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Probabilistic Inverse Modeling: An Application in Hydrology

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The Yakubovich S-Lemma Revisited: Stability and Contractivity in Non-Euclidean Norms

inferred← citeshttps://doi.org/10.1137/24m1689685openalex-snapshot

Regular Pairings for Nonquadratic Lyapunov Functions and Contraction Analysis

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Bringing Engineering Rigor to Deep Learning

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Safety-Assured Design and Adaptation of Learning-Enabled Autonomous Systems

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A Statistical Test for Probabilistic Fairness

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Stability analysis of complementarity systems with neural network controllers

inferred← citeshttps://doi.org/10.1145/3597926.3605231openalex-snapshot

Quantitative Robustness Analysis of Neural Networks

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Adversarial Robustness of Neural Networks from the Perspective of Lipschitz Calculus: A Survey

inferred← citeshttps://doi.org/10.1145/3716863.3718045openalex-snapshot

SAVER: A Toolbox for SAmpling-Based, Probabilistic VERification of Neural Networks

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Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics

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When Deep Learning Meets Polyhedral Theory: A Survey

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Lyapunov-stable neural-network control

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Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems

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Tight Neural Network Verification via Semidefinite Relaxations and Linear Reformulations

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Iteratively Enhanced Semidefinite Relaxations for Efficient Neural Network Verification

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A Semidefinite Relaxation Based Branch-and-Bound Method for Tight Neural Network Verification

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Performance Bounds for Neural Network Estimators: Applications in Fault Detection

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Learning to be safe, in finite time

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Non-Euclidean Contractivity of Recurrent Neural Networks

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Learning Neural Networks under Input-Output Specifications

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Reachability Set Analysis of Closed-Loop Nonlinear Systems with Neural Network Controllers

inferred← citeshttps://doi.org/10.23919/acc53348.2022.9867585openalex-snapshot

Sparsity Promoting Fixed-Order ℋ2-Conic Control

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Modeling Dynamical Systems with Neural Hybrid System Framework via Maximum Entropy Approach

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Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

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Tailored Output Layers of Neural Networks for Satisfaction of State Constraints in Nonlinear Control Systems

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Reachability Analysis and Safety Verification of Neural Feedback Systems via Hybrid Zonotopes

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A Transition System Abstraction Framework for Neural Network Dynamical System Models

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Hybrid Zonotope-Based Backward Reachability Analysis for Neural Feedback Systems With Nonlinear Plant Models

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RNN Controller for Lane-Keeping Systems with Robustness and Safety Verification

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Lyapunov Neural Network with Region of Attraction Search

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Stability Margins of Neural Network Controllers*

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Safe Physics-informed Machine Learning for Dynamics and Control

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Polytopic Input Constraints in Learning-Based Optimal Control Using Neural Networks

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Integral Quadratic Constraints for Neural Networks

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Local Lipschitz Constant Computation of ReLU-FNNs: Upper Bound Computation with Exactness Verification

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A mixed-integer framework for analyzing neural network-based controllers for piecewise affine systems with bounded disturbances

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Signal Denoising Using a New Class of Robust Neural Networks

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Robustra: Training Provable Robust Neural Networks over Reference Adversarial Space

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Efficient Neural Network Verification via Layer-based Semidefinite Relaxations and Linear Cuts

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Towards Scalable Complete Verification of Relu Neural Networks via Dependency-based Branching

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Advanced model predictive control techniques in real-time operation and control of power systems

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Winsorization for Robust Bayesian Neural Networks

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Design and Assurance of Safety-Critical Systems with Artificial Intelligence in FPGAs: The Safety ArtISt Method and a Case Study of an FPGA-Based Autonomous Vehicle Braking Control System

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Certified Neural Network Control Architectures: Methodological Advances in Stability, Robustness, and Cross-Domain Applications

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Formal Verification of Neural Networks via Optimization Methods

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