47 citations · 172 across the 92 of their papers we have counts for
17 papers · 1 filter
Learning a Better Control Barrier Function Under Uncertain Dynamics
Bolun Dai, Prashanth Krishnamurthy, Farshad Khorrami
Using control barrier functions (CBFs) as safety filters provides a computationally inexpensive yet effective method for constructing controllers in safety-critical applications. H…
LipSim: A Provably Robust Perceptual Similarity Metric
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy +2
Recent years have seen growing interest in developing and applying perceptual similarity metrics. Research has shown the superiority of perceptual metrics over pixel-wise metrics i…
High-Dimensional Controller Tuning through Latent Representations
Alireza Sarmadi, Prashanth Krishnamurthy, Farshad Khorrami
In this paper, we propose a method to automatically and efficiently tune high-dimensional vectors of controller parameters. The proposed method first learns a mapping from the high…
Differentiable Optimization Based Time-Varying Control Barrier Functions for Dynamic Obstacle Avoidance
Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy +1
Control barrier functions (CBFs) provide a simple yet effective way for safe control synthesis. Recently, work has been done using differentiable optimization (diffOpt) based metho…
Safe Aerial Manipulator Maneuvering and Force Exertion via Control Barrier Functions
Dimitris Chaikalis, Vinicius Goncalves, Nikolaos Evangeliou +2
This article introduces a safe control strategy for application of forces to an external object using a dexterous robotic arm mounted on an unmanned Aerial Vehicle (UAV). A hybrid…
R-LPIPS: An Adversarially Robust Perceptual Similarity Metric
Sara Ghazanfari, Siddharth Garg, Prashanth Krishnamurthy +2
Similarity metrics have played a significant role in computer vision to capture the underlying semantics of images. In recent years, advanced similarity metrics, such as the Learne…
Using Circulation to Mitigate Spurious Equilibria in Control Barrier Function -- Extended Version
Vinicius Mariano Goncalves, Prashanth Krishnamurthy, Anthony Tzes +1
Control Barrier Functions and Quadratic Programming are increasingly used for designing controllers that consider critical safety constraints. However, like Artificial Potential Fi…
Differential Analysis of Triggers and Benign Features for Black-Box DNN Backdoor Detection
Hao Fu, Prashanth Krishnamurthy, Siddharth Garg +1
This paper proposes a data-efficient detection method for deep neural networks against backdoor attacks under a black-box scenario. The proposed approach is motivated by the intuit…
Towards Better Certified Segmentation via Diffusion Models
Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon +4
The robustness of image segmentation has been an important research topic in the past few years as segmentation models have reached production-level accuracy. However, like classif…
State Constrained Stochastic Optimal Control for Continuous and Hybrid Dynamical Systems Using DFBSDE
Bolun Dai, Prashanth Krishnamurthy, Andrew Papanicolaou +1
We develop a computationally efficient learning-based forward-backward stochastic differential equations (FBSDE) controller for both continuous and hybrid dynamical (HD) systems su…
REMaQE: Reverse Engineering Math Equations from Executables
Meet Udeshi, Prashanth Krishnamurthy, Hammond Pearce +2
Cybersecurity attacks on embedded devices for industrial control systems and cyber-physical systems may cause catastrophic physical damage as well as economic loss. This could be a…
Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions
Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy +3
Control barrier functions (CBFs) have been widely applied to safety-critical robotic applications. However, the construction of control barrier functions for robotic systems remain…
Neural Lyapunov Control for Nonlinear Systems with Unstructured Uncertainties
Shiqing Wei, Prashanth Krishnamurthy, Farshad Khorrami
Stabilizing controller design and region of attraction (RoA) estimation are essential in nonlinear control. Moreover, it is challenging to implement a control Lyapunov function (CL…
Data-Efficient Control Barrier Function Refinement
Bolun Dai, Heming Huang, Prashanth Krishnamurthy +1
Control barrier functions (CBFs) have been widely used for synthesizing controllers in safety-critical applications. When used as a safety filter, it provides a simple and computat…
Data-Driven Deep Learning Based Feedback Linearization of Systems with Unknown Dynamics
Raktim Gautam Goswami, Prashanth Krishnamurthy, Farshad Khorrami
A methodology is developed to learn a feedback linearization (i.e., nonlinear change of coordinates and input transformation) using a data-driven approach for a single input contro…
A Deep Neural Network Algorithm for Linear-Quadratic Portfolio Optimization with MGARCH and Small Transaction Costs
Andrew Papanicolaou, Hao Fu, Prashanth Krishnamurthy +1
We analyze a fixed-point algorithm for reinforcement learning (RL) of optimal portfolio mean-variance preferences in the setting of multivariate generalized autoregressive conditio…
An Optimal Control Strategy for Execution of Large Stock Orders Using LSTMs
A. Papanicolaou, H. Fu, P. Krishnamurthy +2
In this paper, we simulate the execution of a large stock order with real data and general power law in the Almgren and Chriss model. The example that we consider is the liquidatio…