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ORCIDGeorge J. Pappas
Person information
- affiliation: University of Pennsylvania, Philadelphia, PA, USA
- award (2002): Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2023
[j138]Alëna Rodionova
, Lars Lindemann, Manfred Morari, George J. Pappas:
Combined Left and Right Temporal Robustness for Control Under STL Specifications. IEEE Control. Syst. Lett. 7: 619-624 (2023)- [j137]Nicolò Dal Fabbro, Aritra Mitra, George J. Pappas:
Federated TD Learning Over Finite-Rate Erasure Channels: Linear Speedup Under Markovian Sampling. IEEE Control. Syst. Lett. 7: 2461-2466 (2023) - [j136]Lars Lindemann, Matthew Cleaveland, Gihyun Shim, George J. Pappas:
Safe Planning in Dynamic Environments Using Conformal Prediction. IEEE Robotics Autom. Lett. 8(8): 5116-5123 (2023) - [j135]Anastasios Tsiamis, George J. Pappas:
Online Learning of the Kalman Filter With Logarithmic Regret. IEEE Trans. Autom. Control. 68(5): 2774-2789 (2023) - [j134]Alëna Rodionova, Lars Lindemann, Manfred Morari, George J. Pappas:
Temporal Robustness of Temporal Logic Specifications: Analysis and Control Design. ACM Trans. Embed. Comput. Syst. 22(1): 13:1-13:44 (2023) - [j133]Lars Lindemann, Lejun Jiang, Nikolai Matni, George J. Pappas:
Risk of Stochastic Systems for Temporal Logic Specifications. ACM Trans. Embed. Comput. Syst. 22(3): 54:1-54:31 (2023) - [j132]Yukun Yuan, Desheng Zhang, Fei Miao, John A. Stankovic, Tian He, George J. Pappas, Shan Lin:
: Mobility-Driven Integration of Heterogeneous Urban Cyber-Physical Systems Under Disruptive Events. IEEE Trans. Mob. Comput. 22(2): 906-922 (2023) - [j131]Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How:
Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams. IEEE Trans. Robotics 39(4): 2585-2602 (2023) - [c361]Austin K. Chen, Bryce L. Ferguson, Daigo Shishika, Michael R. Dorothy, Jason R. Marden, George J. Pappas, Vijay Kumar:
Path Defense in Dynamic Defender-Attacker Blotto Games (dDAB) with Limited Information. ACC 2023: 447-453 - [c360]Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas:
Conformal Prediction for STL Runtime Verification. ICCPS 2023: 142-153 - [c359]Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris:
Variational Autoencoding Neural Operators. ICML 2023: 30491-30522 - [c358]Samarth Kalluraya, George J. Pappas, Yiannis Kantaros:
Multi-Robot Mission Planning in Dynamic Semantic Environments. ICRA 2023: 1630-1637 - [c357]Mariliza Tzes, Nikolaos Bousias, Evangelos Chatzipantazis, George J. Pappas:
Graph Neural Networks for Multi-Robot Active Information Acquisition. ICRA 2023: 3497-3503 - [c356]Matthew Malencia, George J. Pappas, Vijay Kumar:
Socially Fair Coverage Control. ICRA 2023: 7656-7662 - [c355]Anushri Dixit, Lars Lindemann, Skylar X. Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick:
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents. L4DC 2023: 300-314 - [c354]Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Yannis G. Kevrekidis, Mahyar Fazlyab:
Certified Invertibility in Neural Networks via Mixed-Integer Programming. L4DC 2023: 483-496 - [c353]Thomas Beckers, Qirui Wu, George J. Pappas:
Physics-enhanced Gaussian Process Variational Autoencoder. L4DC 2023: 521-533 - [c352]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. L4DC 2023: 1387-1399 - [c351]Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar:
Active Collaborative Localization in Heterogeneous Robot Teams. Robotics: Science and Systems 2023 - [e6]Nikolai Matni, Manfred Morari, George J. Pappas:
Learning for Dynamics and Control Conference, L4DC 2023, 15-16 June 2023, Philadelphia, PA, USA. Proceedings of Machine Learning Research 211, PMLR 2023 [contents] - [i166]Aritra Mitra, George J. Pappas, Hamed Hassani:
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. CoRR abs/2301.00944 (2023) - [i165]Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Ioannis G. Kevrekidis, Mahyar Fazlyab:
Certified Invertibility in Neural Networks via Mixed-Integer Programming. CoRR abs/2301.11783 (2023) - [i164]Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. CoRR abs/2302.02212 (2023) - [i163]Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris:
Variational Autoencoding Neural Operators. CoRR abs/2302.10351 (2023) - [i162]Shuo Yang, George J. Pappas, Rahul Mangharam, Lars Lindemann:
Safe Perception-Based Control under Stochastic Sensor Uncertainty using Conformal Prediction. CoRR abs/2304.00194 (2023) - [i161]Matthew Cleaveland, Insup Lee, George J. Pappas, Lars Lindemann:
Conformal Prediction Regions for Time Series using Linear Complementarity Programming. CoRR abs/2304.01075 (2023) - [i160]Samarth Kalluraya, George J. Pappas, Yiannis Kantaros:
Resilient Temporal Logic Planning in the Presence of Robot Failures. CoRR abs/2305.05485 (2023) - [i159]Nicolò Dal Fabbro, Aritra Mitra, George J. Pappas:
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling. CoRR abs/2305.08104 (2023) - [i158]Thomas Beckers, Qirui Wu, George J. Pappas:
Physics-enhanced Gaussian Process Variational Autoencoder. CoRR abs/2305.09006 (2023) - [i157]Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas:
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CoRR abs/2305.09017 (2023) - [i156]Thomas Beckers, Tom Z. Jiahao, George J. Pappas:
Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification. CoRR abs/2305.09689 (2023) - [i155]Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni:
The noise level in linear regression with dependent data. CoRR abs/2305.11165 (2023) - [i154]Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar:
Active Collaborative Localization in Heterogeneous Robot Teams. CoRR abs/2305.18193 (2023) - [i153]Alëna Rodionova, Lars Lindemann, Manfred Morari, George J. Pappas:
Combined Left and Right Temporal Robustness for Control under STL Specifications. CoRR abs/2306.04936 (2023) - [i152]Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher:
Adversarial Training Should Be Cast as a Non-Zero-Sum Game. CoRR abs/2306.11035 (2023) - [i151]Kong Yao Chee, Thales C. Silva, M. Ani Hsieh, George J. Pappas:
Enhancing Sample Efficiency and Uncertainty Compensation in Learning-based Model Predictive Control for Aerial Robots. CoRR abs/2308.00570 (2023) - [i150]Igor Spasojevic, Xu Liu, Ankit Prabhu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar:
Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles. CoRR abs/2308.06658 (2023) - [i149]Shaoru Chen, Kong Yao Chee, Nikolai Matni, M. Ani Hsieh, George J. Pappas:
Safety Filter Design for Neural Network Systems via Convex Optimization. CoRR abs/2308.08086 (2023) - [i148]Ingvar M. Ziemann, Anastasios Tsiamis, Bruce D. Lee, Yassir Jedra, Nikolai Matni, George J. Pappas:
A Tutorial on the Non-Asymptotic Theory of System Identification. CoRR abs/2309.03873 (2023) - [i147]Zhirui Dai, Arash Asgharivaskasi, Thai Duong, Shusen Lin, Maria-Elizabeth Tzes, George J. Pappas, Nikolay Atanasov:
Optimal Scene Graph Planning with Large Language Model Guidance. CoRR abs/2309.09182 (2023) - 2022
- [j130]Matthew Cleaveland, Lars Lindemann, Radoslav Ivanov, George J. Pappas:
Risk verification of stochastic systems with neural network controllers. Artif. Intell. 313: 103782 (2022) - [j129]Thomas Beckers, Leonardo J. Colombo, Sandra Hirche, George J. Pappas:
Online Learning-Based Trajectory Tracking for Underactuated Vehicles With Uncertain Dynamics. IEEE Control. Syst. Lett. 6: 2090-2095 (2022) - [j128]Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris:
Learning Operators with Coupled Attention. J. Mach. Learn. Res. 23: 215:1-215:63 (2022) - [j127]Mahyar Fazlyab, Manfred Morari, George J. Pappas:
Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming. IEEE Trans. Autom. Control. 67(1): 1-15 (2022) - [j126]Vasileios Tzoumas, Ali Jadbabaie, George J. Pappas:
Robust and Adaptive Sequential Submodular Optimization. IEEE Trans. Autom. Control. 67(1): 89-104 (2022) - [j125]Lars Lindemann, George J. Pappas, Dimos V. Dimarogonas:
Reactive and Risk-Aware Control for Signal Temporal Logic. IEEE Trans. Autom. Control. 67(10): 5262-5277 (2022) - [j124]Andreea B. Alexandru, George J. Pappas:
Private Weighted Sum Aggregation. IEEE Trans. Control. Netw. Syst. 9(1): 219-230 (2022) - [j123]Brent Schlotfeldt, Vasileios Tzoumas, George J. Pappas:
Resilient Active Information Acquisition With Teams of Robots. IEEE Trans. Robotics 38(1): 244-261 (2022) - [j122]Yiannis Kantaros, Samarth Kalluraya, Qi Jin, George J. Pappas:
Perception-Based Temporal Logic Planning in Uncertain Semantic Maps. IEEE Trans. Robotics 38(4): 2536-2556 (2022) - [j121]Lifeng Zhou, Vasileios Tzoumas, George J. Pappas, Pratap Tokekar:
Distributed Attack-Robust Submodular Maximization for Multirobot Planning. IEEE Trans. Robotics 38(5): 3097-3112 (2022) - [c350]Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas:
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CDC 2022: 1447-1453 - [c349]Anastasia Impicciatore, Anastasios Tsiamis, Yuriy Zacchia Lun, Alessandro D'Innocenzo, George J. Pappas:
Secure state estimation over Markov wireless communication channels. CDC 2022: 2935-2940 - [c348]Anton Xue, Lars Lindemann, Alexander Robey, Hamed Hassani, George J. Pappas, Rajeev Alur:
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks. CDC 2022: 3389-3396 - [c347]Arman Adibi, Aritra Mitra, George J. Pappas, Hamed Hassani:
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. CDC 2022: 4179-4184 - [c346]Thomas Beckers, Leonardo J. Colombo, Manfred Morari, George J. Pappas:
Learning-based Balancing of Model-based and Feedback Control for Second-order Mechanical Systems. CDC 2022: 4667-4673 - [c345]Orlando Romero, Mouhacine Benosman, George J. Pappas:
ODE Discretization Schemes as Optimization Algorithms. CDC 2022: 6318-6325 - [c344]Thomas Beckers, George J. Pappas, Leonardo J. Colombo:
Learning Rigidity-based Flocking Control using Gaussian Processes with Probabilistic Stability Guarantees. CDC 2022: 7254-7259 - [c343]Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas:
Learning to Control Linear Systems can be Hard. COLT 2022: 3820-3857 - [c342]Lars Lindemann, Alëna Rodionova, George J. Pappas:
Temporal Robustness of Stochastic Signals. HSCC 2022: 10:1-10:11 - [c341]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do deep networks transfer invariances across classes? ICLR 2022 - [c340]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average and Worst-case Performance. ICML 2022: 18667-18686 - [c339]Mariliza Tzes, Vasileios Vasilopoulos, Yiannis Kantaros, George J. Pappas:
Reactive Informative Planning for Mobile Manipulation Tasks under Sensing and Environmental Uncertainty. ICRA 2022: 7320-7326 - [c338]Matthew Malencia, Sandeep Manjanna, M. Ani Hsieh, George J. Pappas, Vijay Kumar:
Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR). IROS 2022: 8762-8769 - [c337]Charis J. Stamouli, Anastasios Tsiamis, Manfred Morari, George J. Pappas:
Adaptive Stochastic MPC under Unknown Noise Distribution. L4DC 2022: 596-607 - [c336]Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf:
Probable Domain Generalization via Quantile Risk Minimization. NeurIPS 2022 - [c335]Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani:
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. NeurIPS 2022 - [c334]Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas:
NOMAD: Nonlinear Manifold Decoders for Operator Learning. NeurIPS 2022 - [i146]Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris:
Learning Operators with Coupled Attention. CoRR abs/2201.01032 (2022) - [i145]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average- and Worst-case Performance. CoRR abs/2202.01136 (2022) - [i144]Lars Lindemann, Alëna Rodionova, George J. Pappas:
Temporal Robustness of Stochastic Signals. CoRR abs/2202.02583 (2022) - [i143]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. CoRR abs/2203.01198 (2022) - [i142]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do Deep Networks Transfer Invariances Across Classes? CoRR abs/2203.09739 (2022) - [i141]Alëna Rodionova, Lars Lindemann, Manfred Morari, George J. Pappas:
Temporal Robustness of Temporal Logic Specifications: Analysis and Control Design. CoRR abs/2203.15661 (2022) - [i140]Anton Xue, Lars Lindemann, Alexander Robey, Hamed Hassani, George J. Pappas, Rajeev Alur:
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks. CoRR abs/2204.00846 (2022) - [i139]Charis J. Stamouli, Anastasios Tsiamis, Manfred Morari, George J. Pappas:
Adaptive Stochastic MPC under Unknown Noise Distribution. CoRR abs/2204.01107 (2022) - [i138]Arman Adibi, Aritra Mitra, George J. Pappas, Hamed Hassani:
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. CoRR abs/2204.03187 (2022) - [i137]Austin K. Chen, Bryce L. Ferguson, Daigo Shishika, Michael R. Dorothy, Jason R. Marden, George J. Pappas, Vijay Kumar:
Path Defense in Dynamic Defender-Attacker Blotto Games (dDAB) with Limited Information. CoRR abs/2204.04176 (2022) - [i136]Mariliza Tzes, Vasileios Vasilopoulos, Yiannis Kantaros, George J. Pappas:
Reactive Informative Planning for Mobile Manipulation Tasks under Sensing and Environmental Uncertainty. CoRR abs/2205.06301 (2022) - [i135]Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas:
Learning to Control Linear Systems can be Hard. CoRR abs/2205.14035 (2022) - [i134]Lars Lindemann, Lejun Jiang, Nikolai Matni, George J. Pappas:
Risk of Stochastic Systems for Temporal Logic Specifications. CoRR abs/2205.14523 (2022) - [i133]Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani:
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. CoRR abs/2206.02834 (2022) - [i132]Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas:
NOMAD: Nonlinear Manifold Decoders for Operator Learning. CoRR abs/2206.03551 (2022) - [i131]Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett:
Toward Certified Robustness Against Real-World Distribution Shifts. CoRR abs/2206.03669 (2022) - [i130]Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf:
Probable Domain Generalization via Quantile Risk Minimization. CoRR abs/2207.09944 (2022) - [i129]Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How:
Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams. CoRR abs/2208.00262 (2022) - [i128]Matthew Malencia, Sandeep Manjanna, M. Ani Hsieh, George J. Pappas, Vijay Kumar:
Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR). CoRR abs/2208.06053 (2022) - [i127]Kelsey Saulnier, Lifeng Zhou, George J. Pappas, Vijay Kumar:
Resilient Consensus via Voronoi Communication Graphs. CoRR abs/2209.04381 (2022) - [i126]Anastasia Impicciatore, Anastasios Tsiamis, Yuriy Zacchia Lun, Alessandro D'Innocenzo, George J. Pappas:
Secure state estimation over Markov wireless communication channels (extended version). CoRR abs/2209.05146 (2022) - [i125]Anastasios Tsiamis, Ingvar M. Ziemann, Nikolai Matni, George J. Pappas:
Statistical Learning Theory for Control: A Finite Sample Perspective. CoRR abs/2209.05423 (2022) - [i124]Samarth Kalluraya, George J. Pappas, Yiannis Kantaros:
Multi-robot Mission Planning in Dynamic Semantic Environments. CoRR abs/2209.06323 (2022) - [i123]Matthew Cleaveland, Lars Lindemann, Radoslav Ivanov, George J. Pappas:
Risk Verification of Stochastic Systems with Neural Network Controllers. CoRR abs/2209.09881 (2022) - [i122]Mariliza Tzes, Nikolaos Bousias, Evangelos Chatzipantazis, George J. Pappas:
Graph Neural Networks for Multi-Robot Active Information Acquisition. CoRR abs/2209.12091 (2022) - [i121]Lars Lindemann, Matthew Cleaveland, Gihyun Shim, George J. Pappas:
Safe Planning in Dynamic Environments using Conformal Prediction. CoRR abs/2210.10254 (2022) - [i120]Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas:
Conformal Prediction for STL Runtime Verification. CoRR abs/2211.01539 (2022) - [i119]Anushri Dixit, Lars Lindemann, Skylar Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick:
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents. CoRR abs/2212.00278 (2022) - 2021
- [j120]Yiannis Kantaros, Brent Schlotfeldt, Nikolay Atanasov, George J. Pappas:
Sampling-based planning for non-myopic multi-robot information gathering. Auton. Robots 45(7): 1029-1046 (2021) - [j119]Konstantinos Gatsis, George J. Pappas:
Statistical learning for analysis of networked control systems over unknown channels. Autom. 125: 109386 (2021) - [j118]George J. Pappas, Kostas Daniilidis, Leonidas J. Guibas, Lydia E. Kavraki, Petros Koumoutsakos, Kostas J. Kyriakopoulos, John Lygeros, Michael S. Triantafyllou, Panagiotis Tsiotras:
Robotics in the AI era: A vision for a Hellenic Robotics Initiative. Found. Trends Robotics 9(3): 201-265 (2021) - [j117]Jason Z. Kim, Zhixin Lu, Erfan Nozari, George J. Pappas, Danielle S. Bassett:
Teaching recurrent neural networks to infer global temporal structure from local examples. Nat. Mach. Intell. 3(4): 316-323 (2021) - [j116]Matthew Malencia, Vijay Kumar, George J. Pappas, Amanda Prorok:
Fair Robust Assignment Using Redundancy. IEEE Robotics Autom. Lett. 6(2): 4217-4224 (2021) - [j115]Luiz F. O. Chamon, George J. Pappas, Alejandro Ribeiro:
Approximate Supermodularity of Kalman Filter Sensor Selection. IEEE Trans. Autom. Control. 66(1): 49-63 (2021) - [j114]Konstantinos Gatsis, Hamed Hassani, George J. Pappas:
Latency-Reliability Tradeoffs for State Estimation. IEEE Trans. Autom. Control. 66(3): 1009-1023 (2021) - [j113]Vasileios Tzoumas, Luca Carlone, George J. Pappas, Ali Jadbabaie:
LQG Control and Sensing Co-Design. IEEE Trans. Autom. Control. 66(4): 1468-1483 (2021) - [j112]Andreea B. Alexandru, Konstantinos Gatsis, Yasser Shoukry, Sanjit A. Seshia, Paulo Tabuada, George J. Pappas:
Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption. IEEE Trans. Autom. Control. 66(5): 2357-2364 (2021) - [j111]Jingqi Li, Ximing Chen, Sérgio Pequito, George J. Pappas, Victor M. Preciado:
On the Structural Target Controllability of Undirected Networks. IEEE Trans. Autom. Control. 66(10): 4836-4843 (2021) - [j110]Fei Miao, Sihong He, Lynn Pepin, Shuo Han, Abdeltawab M. Hendawi, Mohamed E. Khalefa, John A. Stankovic, George J. Pappas:
Data-driven Distributionally Robust Optimization For Vehicle Balancing of Mobility-on-Demand Systems. ACM Trans. Cyber Phys. Syst. 5(2): 17:1-17:27 (2021) - [j109]Radoslav Ivanov, Taylor J. Carpenter, James Weimer, Rajeev Alur, George J. Pappas, Insup Lee:
Verifying the Safety of Autonomous Systems with Neural Network Controllers. ACM Trans. Embed. Comput. Syst. 20(1): 7:1-7:26 (2021) - [j108]Ke Sun, Brent Schlotfeldt, George J. Pappas, Vijay Kumar:
Stochastic Motion Planning Under Partial Observability for Mobile Robots With Continuous Range Measurements. IEEE Trans. Robotics 37(3): 979-995 (2021) - [c333]Bruno Augusto Angélico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas:
Source Seeking in Unknown Environments with Convex Obstacles. ACC 2021: 5055-5061 - [c332]Radoslav Ivanov, Taylor J. Carpenter, James Weimer, Rajeev Alur, George J. Pappas, Insup Lee:
Verisig 2.0: Verification of Neural Network Controllers Using Taylor Model Preconditioning. CAV (1) 2021: 249-262 - [c331]Alëna Rodionova, Lars Lindemann, Manfred Morari, George J. Pappas:
Time-Robust Control for STL Specifications. CDC 2021: 572-579 - [c330]Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Federated Learning with Incrementally Aggregated Gradients. CDC 2021: 775-782 - [c329]Lars Lindemann, Nikolai Matni, George J. Pappas:
STL Robustness Risk over Discrete-Time Stochastic Processes. CDC 2021: 1329-1335 - [c328]Anastasios Tsiamis, George J. Pappas:
Linear Systems can be Hard to Learn. CDC 2021: 2903-2910 - [c327]Aritra Mitra, Hamed Hassani, George J. Pappas:
Online Federated Learning.