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2020 – today
- 2024
[c159]Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu:
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels. ICLR 2024- [c158]Luigi Berducci, Shuo Yang, Rahul Mangharam, Radu Grosu:
Learning Adaptive Safety for Multi-Agent Systems. ICRA 2024: 2859-2865 - [c157]Andreas Brandstätter, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari, Radu Grosu:
Flock-Formation Control of Multi-Agent Systems using Imperfect Relative Distance Measurements. ICRA 2024: 12193-12200 - [c156]Mónika Farsang, Mathias Lechner, David Lung, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Learning with Chemical versus Electrical Synapses Does it Make a Difference? ICRA 2024: 15106-15112 - [c155]Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu:
Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields. WACV 2024: 8201-8210 - [i72]Mónika Farsang, Mathias Lechner, David Lung, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Learning with Chemical versus Electrical Synapses - Does it Make a Difference? CoRR abs/2401.08602 (2024) - [i71]Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu:
Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields. CoRR abs/2401.10178 (2024) - [i70]Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu:
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels. CoRR abs/2401.14469 (2024) - [i69]Mónika Farsang, Radu Grosu:
Gated Chemical Units. CoRR abs/2403.08791 (2024) - [i68]Axel Brunnbauer, Luigi Berducci, Peter Priller, Dejan Nickovic, Radu Grosu:
Scenario-Based Curriculum Generation for Multi-Agent Autonomous Driving. CoRR abs/2403.17805 (2024) - [i67]Elpiniki Maria Lygizou, Michael Reiter, Margarita Maurer-Granofszky, Michael N. Dworzak, Radu Grosu:
Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers. CoRR abs/2406.18309 (2024) - [i66]Shrajan Bhandary, Dejan Kuhn, Zahra Babaiee, Tobias Fechter, Simon Spohn, Constantinos Zamboglou, Anca-Ligia Grosu, Radu Grosu:
Segmentation of Prostate Tumour Volumes from PET Images is a Different Ball Game. CoRR abs/2407.10537 (2024) - 2023
- [j35]Shrajan Bhandary, Dejan Kuhn, Zahra Babaiee, Tobias Fechter, Matthias Benndorf
, Constantinos Zamboglou, Anca-Ligia Grosu, Radu Grosu:
Investigation and benchmarking of U-Nets on prostate segmentation tasks. Comput. Medical Imaging Graph. 107: 102241 (2023) - [j34]Christian Hirsch, Luca Davoli, Radu Grosu, Gianluigi Ferrari:
DynGATT: A dynamic GATT-based data synchronization protocol for BLE networks. Comput. Networks 222: 109560 (2023) - [j33]Usama Mehmood, Shouvik Roy, Amol Damare, Radu Grosu, Scott A. Smolka, Scott D. Stoller:
A distributed simplex architecture for multi-agent systems. J. Syst. Archit. 134: 102784 (2023) - [j32]Luca Cardelli, Radu Grosu, Kim Guldstrand Larsen, Mirco Tribastone, Max Tschaikowski, Andrea Vandin:
Algorithmic Minimization of Uncertain Continuous-Time Markov Chains. IEEE Trans. Autom. Control. 68(11): 6557-6572 (2023) - [c154]Jie He, Dejan Nickovic, Ezio Bartocci, Radu Grosu:
TD-Magic: From Pictures of Timing Diagrams To Formal Specifications. DAC 2023: 1-6 - [c153]Xabier Iturbe, Nassim Abderrahmane, Jaume Abella, Sergi Alcaide, Eric Beyne, Henri-Pierre Charles, Christelle Charpin-Nicolle, Lars Chittka, Angélica Dávila, Arne Erdmann, Carles Estrada, Ander Fernández, Anna Fontanelli, José Flich, Gianluca Furano, Alejandro Hernán Gloriani, Erik Isusquiza, Radu Grosu, Carles Hernández, Daniele Ielmini, David Jackson, Maha Kooli, Nicola Lepri, Bernabé Linares-Barranco, Jean-Loup Lachese, Eric Laurent, Menno Lindwer, Frank Linsenmaier, Mikel Luján, Karel Masarík, Nele Mentens, Orlando Moreira, Chinmay Nawghane, Luca Peres, Jean-Philippe Noel, Arash Pourtaherian, Christoph Posch, Peter Priller, Zdenek Prikryl, Felix Resch, Oliver Rhodes, Todor P. Stefanov, Moritz Storring, Michele Taliercio, Rafael Tornero, Marcel D. van de Burgwal, Geert Van der Plas, Elisa Vianello, Pavel Zaykov:
NimbleAI: Towards Neuromorphic Sensing-Processing 3D-integrated Chips. DATE 2023: 1-6 - [c152]Andreas Brandstätter, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari, Radu Grosu:
Multi-Agent Spatial Predictive Control with Application to Drone Flocking. ICRA 2023: 1221-1227 - [i65]Julian Lemmel, Radu Grosu:
On the Benefits of Biophysical Synapses. CoRR abs/2303.04944 (2023) - [i64]Sophie A. Neubauer, Radu Grosu:
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques. CoRR abs/2308.12192 (2023) - [i63]Julian Lemmel, Zahra Babaiee, Marvin Kleinlehner, Ivan Majic, Philipp Neubauer, Johannes Scholz, Radu Grosu, Sophie A. Neubauer:
Prediction of Tourism Flow with Sparse Geolocation Data. CoRR abs/2308.14516 (2023) - [i62]Daniel Scheuchenstuhl, Stefan Ulmer, Felix Resch, Luigi Berducci, Radu Grosu:
Enhancing Robot Learning through Learned Human-Attention Feature Maps. CoRR abs/2308.15327 (2023) - [i61]Luigi Berducci, Shuo Yang, Rahul Mangharam, Radu Grosu:
Learning Adaptive Safety for Multi-Agent Systems. CoRR abs/2309.10657 (2023) - [i60]Julian Lemmel, Radu Grosu:
Real-Time Recurrent Reinforcement Learning. CoRR abs/2311.04830 (2023) - 2022
- [j31]Paul Bogdan, Radu Grosu, Insup Lee:
Introduction to the Special Issue on Internet-of-Medical-Things. ACM Trans. Comput. Heal. 3(3): 26e:1 (2022) - [j30]Penghua Li, Yifeng Yang, Radu Grosu, Guodong Wang, Rui Li, Yuehong Wu, Zeng Huang:
Driver Distraction Detection Using Octave-Like Convolutional Neural Network. IEEE Trans. Intell. Transp. Syst. 23(7): 8823-8833 (2022) - [c151]Sophie A. Gruenbacher, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu:
GoTube: Scalable Statistical Verification of Continuous-Depth Models. AAAI 2022: 6755-6764 - [c150]Sophie A. Neubauer, Radu Grosu:
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques. Principles of Systems Design 2022: 625-649 - [c149]Radu Grosu:
Keynote Lecture Towards Neuro-Symbolic AI. ICCP 2022: vii - [c148]Hamidreza Mahyar, Peter Tulala, Elahe Ghalebi, Radu Grosu:
DeepWafer: A Generative Wafermap Model with Deep Adversarial Networks. ICMLA 2022: 126-131 - [c147]Axel Brunnbauer, Luigi Berducci, Andreas Brandstätter, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing. ICRA 2022: 7513-7520 - [c146]Jie He, Ezio Bartocci, Dejan Nickovic, Haris Isakovic, Radu Grosu:
DeepSTL - From English Requirements to Signal Temporal Logic. ICSE 2022: 610-622 - [c145]Andreas Brandstätter, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari, Radu Grosu:
Towards Drone Flocking Using Relative Distance Measurements. ISoLA (3) 2022: 97-109 - [c144]Luigi Berducci, Radu Grosu:
Safe Policy Improvement in Constrained Markov Decision Processes. ISoLA (1) 2022: 360-381 - [i59]Andreas Brandstätter, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari, Radu Grosu:
Multi-Agent Spatial Predictive Control with Application to Drone Flocking (Extended Version). CoRR abs/2203.16960 (2022) - [i58]Zahra Babaiee, Lucas Liebenwein, Ramin M. Hasani, Daniela Rus, Radu Grosu:
End-to-End Sensitivity-Based Filter Pruning. CoRR abs/2204.07412 (2022) - [i57]Mathias Lechner, Ramin M. Hasani, Zahra Babaiee, Radu Grosu, Daniela Rus, Thomas A. Henzinger, Sepp Hochreiter:
Entangled Residual Mappings. CoRR abs/2206.01261 (2022) - [i56]Julian Lemmel, Zahra Babaiee, Marvin Kleinlehner, Ivan Majic, Philipp Neubauer, Johannes Scholz, Radu Grosu, Sophie A. Neubauer:
Deep-Learning vs Regression: Prediction of Tourism Flow with Limited Data. CoRR abs/2206.13274 (2022) - [i55]Zahra Babaiee, Lucas Liebenwein, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Pruning by Active Attention Manipulation. CoRR abs/2210.11114 (2022) - [i54]Luigi Berducci, Radu Grosu:
Safe Policy Improvement in Constrained Markov Decision Processes. CoRR abs/2210.11259 (2022) - [i53]Shrajan Bhandary, Zahra Babaiee, Dejan Kostyszyn, Tobias Fechter, Constantinos Zamboglou, Anca-Ligia Grosu, Radu Grosu:
IB-U-Nets: Improving medical image segmentation tasks with 3D Inductive Biased kernels. CoRR abs/2210.15949 (2022) - 2021
- [c143]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Liquid Time-constant Networks. AAAI 2021: 7657-7666 - [c142]Sophie Gruenbacher, Ramin M. Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, Radu Grosu:
On the Verification of Neural ODEs with Stochastic Guarantees. AAAI 2021: 11525-11535 - [c141]Shouvik Roy, Usama Mehmood, Radu Grosu, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari:
Distributed Control for Flocking Maneuvers via Acceleration-Weighted Neighborhooding. ACC 2021: 2745-2750 - [c140]Usama Mehmood, Scott D. Stoller, Radu Grosu, Scott A. Smolka:
Collision-Free 3D Flocking Using the Distributed Simplex Architecture. Formal Methods in Outer Space 2021: 147-156 - [c139]Haris Isakovic, Luis Lino Ferreira, Irmin Okic, Adam Dukkon, Zlatan Tucakovic, Radu Grosu:
QoS for Dynamic Deployment of IoT Services. ICIT 2021: 1144-1151 - [c138]Haris Isakovic, Stefan Dangl, Zlatan Tucakovic, Radu Grosu:
Adaptive Signal Filtering Platform for a CPS/IoT Ecosystem. ICIT 2021: 1391-1396 - [c137]Zahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu:
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification. ICML 2021: 478-489 - [c136]Mathias Lechner, Ramin M. Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger:
Adversarial Training is Not Ready for Robot Learning. ICRA 2021: 4140-4147 - [c135]Radu Grosu:
Keynote Lecture : Neural circuit policies. ISPDC 2021: xii - [c134]Luca Cardelli, Radu Grosu, Kim G. Larsen, Mirco Tribastone, Max Tschaikowski, Andrea Vandin:
Lumpability for Uncertain Continuous-Time Markov Chains. QEST 2021: 391-409 - [c133]Usama Mehmood, Scott D. Stoller, Radu Grosu, Shouvik Roy, Amol Damare, Scott A. Smolka:
A Distributed Simplex Architecture for Multi-agent Systems. SETTA 2021: 239-257 - [i52]Axel Brunnbauer, Luigi Berducci, Andreas Brandstätter, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars. CoRR abs/2103.04909 (2021) - [i51]Mathias Lechner, Ramin M. Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger:
Adversarial Training is Not Ready for Robot Learning. CoRR abs/2103.08187 (2021) - [i50]Zahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu:
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification. CoRR abs/2106.07091 (2021) - [i49]Sophie Gruenbacher, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu:
GoTube: Scalable Stochastic Verification of Continuous-Depth Models. CoRR abs/2107.08467 (2021) - [i48]Jie He, Ezio Bartocci, Dejan Nickovic, Haris Isakovic, Radu Grosu:
From English to Signal Temporal Logic. CoRR abs/2109.10294 (2021) - [i47]Edgar A. Aguilar, Luigi Berducci, Axel Brunnbauer, Radu Grosu, Dejan Nickovic:
From STL Rulebooks to Rewards. CoRR abs/2110.02792 (2021) - [i46]Shrajan Bhandary, Zahra Babaiee, Dejan Kostyszyn, Tobias Fechter, Constantinos Zamboglou, Anca L. Grosu, Radu Grosu:
3D-OOCS: Learning Prostate Segmentation with Inductive Bias. CoRR abs/2110.15664 (2021) - 2020
- [j29]Xuelin Zhang, Xiaojian Xu, Xiaobin Xu, Diju Gao, Haibo Gao, Guodong Wang, Radu Grosu:
Intelligent Sea States Identification Based on Maximum Likelihood Evidential Reasoning Rule. Entropy 22(7): 770 (2020) - [j28]Mathias Lechner, Ramin M. Hasani, Alexander Amini, Thomas A. Henzinger, Daniela Rus, Radu Grosu:
Neural circuit policies enabling auditable autonomy. Nat. Mach. Intell. 2(10): 642-652 (2020) - [c132]Shouvik Roy, Usama Mehmood, Radu Grosu, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari:
Learning Distributed Controllers for V-Formation. ACSOS 2020: 119-128 - [c131]Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott A. Smolka, Radu Grosu:
Lagrangian Reachtubes: The Next Generation. CDC 2020: 1556-1563 - [c130]Usama Mehmood, Shouvik Roy, Radu Grosu, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari:
Neural Flocking: MPC-Based Supervised Learning of Flocking Controllers. FoSSaCS 2020: 1-16 - [c129]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits. ICML 2020: 4082-4093 - [c128]Mathias Lechner, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-end Robot Learning Scheme. ICRA 2020: 5446-5452 - [c127]Dung T. Phan, Radu Grosu, Nils Jansen, Nicola Paoletti, Scott A. Smolka, Scott D. Stoller:
Neural Simplex Architecture. NFM 2020: 97-114 - [c126]Haris Isakovic, Edgar Azpiazu Crespo, Radu Grosu:
An Energy Sustainable CPS/IoT Ecosystem. SmartCity360° 2020: 305-322 - [i45]Radu Grosu, Anna Lukina, Scott A. Smolka, Ashish Tiwari, Vasudha Varadarajan, Xingfang Wang:
V-Formation via Model Predictive Control. CoRR abs/2002.08955 (2020) - [i44]Radu Grosu:
ResNets, NeuralODEs and CT-RNNs are Particular Neural Regulatory Networks. CoRR abs/2002.12776 (2020) - [i43]Shouvik Roy, Usama Mehmood, Radu Grosu, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari:
Learning Distributed Controllers for V-Formation. CoRR abs/2006.00680 (2020) - [i42]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Liquid Time-constant Networks. CoRR abs/2006.04439 (2020) - [i41]Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott A. Smolka, Radu Grosu:
Lagrangian Reachtubes: The Next Generation. CoRR abs/2012.07458 (2020) - [i40]Sophie Gruenbacher, Ramin M. Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, Radu Grosu:
On The Verification of Neural ODEs with Stochastic Guarantees. CoRR abs/2012.08863 (2020) - [i39]Usama Mehmood, Scott D. Stoller, Radu Grosu, Shouvik Roy, Amol Damare, Scott A. Smolka:
A Distributed Simplex Architecture for Multi-Agent Systems. CoRR abs/2012.10153 (2020)
2010 – 2019
- 2019
- [j27]Denise Ratasich, Faiq Khalid, Florian Geissler, Radu Grosu, Muhammad Shafique, Ezio Bartocci:
A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems. IEEE Access 7: 13260-13283 (2019) - [j26]Guodong Wang, Anna Ledwoch, Ramin M. Hasani, Radu Grosu, Alexandra Brintrup:
A generative neural network model for the quality prediction of work in progress products. Appl. Soft Comput. 85 (2019) - [j25]Amit Gurung, Rajarshi Ray, Ezio Bartocci, Sergiy Bogomolov, Radu Grosu:
Parallel reachability analysis of hybrid systems in XSpeed. Int. J. Softw. Tools Technol. Transf. 21(4): 401-423 (2019) - [j24]Houssam Abbas, Alëna Rodionova, Konstantinos Mamouras, Ezio Bartocci, Scott A. Smolka, Radu Grosu:
Quantitative Regular Expressions for Arrhythmia Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 16(5): 1586-1597 (2019) - [j23]Md. Ariful Islam, Rance Cleaveland, Flavio H. Fenton, Radu Grosu, Paul L. Jones, Scott A. Smolka:
Probabilistic reachability for multi-parameter bifurcation analysis of cardiac alternans. Theor. Comput. Sci. 765: 158-169 (2019) - [c125]Ramin M. Hasani, Guodong Wang, Radu Grosu:
A Machine Learning Suite for Machine Components' Health-Monitoring. AAAI 2019: 9472-9477 - [c124]Sophie Gruenbacher, Jacek Cyranka, Md. Ariful Islam, Max Tschaikowski, Scott A. Smolka, Radu Grosu:
Under the Hood of a Stand-Alone Lagrangian Reachability Tool. ARCH@CPSIoTWeek 2019: 211-219 - [c123]Mathias Lechner, Ramin M. Hasani, Manuel Zimmer, Thomas A. Henzinger, Radu Grosu:
Designing Worm-inspired Neural Networks for Interpretable Robotic Control. ICRA 2019: 87-94 - [c122]Haris Isakovic, Vanja Bisanovic, Bernhard Wally, Thomas Rausch, Denise Ratasich, Schahram Dustdar, Gerti Kappel, Radu Grosu:
Sensyml: Simulation Environment for large-scale IoT Applications. IECON 2019: 3024-3030 - [c121]Ramin M. Hasani, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, Daniela Rus:
Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks. IJCNN 2019: 1-8 - [c120]Haris Isakovic, Alexander Fasching, Lukas Punzenberger, Radu Grosu:
CPS/IoT Ecosystem: Indoor Vertical Farming System. ISCT 2019: 47-52 - [c119]Christian Hirsch, Ezio Bartocci, Radu Grosu:
Capacitive Soil Moisture Sensor Node for IoT in Agriculture and Home. ISCT 2019: 97-102 - [c118]Anna Lukina, Ashish Tiwari, Scott A. Smolka, Radu Grosu:
Distributed adaptive-neighborhood control for stochastic reachability in multi-agent systems. SAC 2019: 914-921 - [c117]Denise Ratasich, Michael Platzer, Radu Grosu, Ezio Bartocci:
Adaptive Fault Detection Exploiting Redundancy with Uncertainties in Space and Time. SASO 2019: 23-32 - [c116]Dung T. Phan, Nicola Paoletti, Timothy Zhang, Radu Grosu, Scott A. Smolka, Scott D. Stoller:
Neural state classification for hybrid systems. SNR 2019: 24-27 - [p3]Axel Legay, Anna Lukina, Louis-Marie Traonouez, Junxing Yang, Scott A. Smolka, Radu Grosu:
Statistical Model Checking. Computing and Software Science 2019: 478-504 - [e2]Ezio Bartocci, Rance Cleaveland, Radu Grosu, Oleg Sokolsky:
From Reactive Systems to Cyber-Physical Systems - Essays Dedicated to Scott A. Smolka on the Occasion of His 65th Birthday. Lecture Notes in Computer Science 11500, Springer 2019, ISBN 978-3-030-31513-9 [contents] - [i38]Denise Ratasich, Michael Platzer, Radu Grosu, Ezio Bartocci:
Adaptive Fault Detection exploiting Redundancy with Uncertainties in Space and Time. CoRR abs/1903.04326 (2019) - [i37]Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu, Sinead Williamson:
Dynamic Nonparametric Edge-Clustering Model for Time-Evolving Sparse Networks. CoRR abs/1905.11724 (2019) - [i36]Dung T. Phan, Nicola Paoletti, Radu Grosu, Nils Jansen, Scott A. Smolka, Scott D. Stoller:
Neural Simplex Architecture. CoRR abs/1908.00528 (2019) - [i35]Shouvik Roy, Usama Mehmood, Radu Grosu, Scott A. Smolka, Scott D. Stoller, Ashish Tiwari:
Neural Flocking: MPC-based Supervised Learning of Flocking Controllers. CoRR abs/1908.09813 (2019) - [i34]Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu, Graham W. Taylor, Sinead A. Williamson:
A Nonparametric Bayesian Model for Sparse Temporal Multigraphs. CoRR abs/1910.05098 (2019) - 2018
- [j22]Stefan Jaksic, Ezio Bartocci, Radu Grosu, Thang Nguyen, Dejan Nickovic:
Quantitative monitoring of STL with edit distance. Formal Methods Syst. Des. 53(1): 83-112 (2018) - [j21]Hamidreza Mahyar, Rouzbeh Hasheminezhad, Elaheh Ghalebi, Ali Nazemian, Radu Grosu, Ali Movaghar, Hamid R. Rabiee:
Identifying central nodes for information flow in social networks using compressive sensing. Soc. Netw. Anal. Min. 8(1): 33:1-33:24 (2018) - [j20]Stefan Jaksic, Ezio Bartocci, Radu Grosu, Dejan Nickovic:
An Algebraic Framework for Runtime Verification. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(11): 2233-2243 (2018) - [c115]Dung T. Phan, Nicola Paoletti, Timothy Zhang, Radu Grosu, Scott A. Smolka, Scott D. Stoller:
Neural State Classification for Hybrid Systems. ATVA 2018: 422-440 - [c114]Radu Grosu, Elahe Ghalebi K., Ali Movaghar, Hamidreza Mahyar:
Compressed Sensing in Cyber Physical Social Systems. Principles of Modeling 2018: 287-305 - [c113]Jacek Cyranka, Md. Ariful Islam, Scott A. Smolka, Sicun Gao, Radu Grosu:
Tight Continuous-Time Reachtubes for Lagrangian Reachability. CDC 2018: 6854-6861 - [c112]Hamidreza Mahyar, Rouzbeh Hasheminezhad, Elahe Ghalebi K., Radu Grosu, Harry Eugene Stanley:
A Compressive Sensing Framework for Distributed Detection of High Closeness Centrality Nodes in Networks. COMPLEX NETWORKS (2) 2018: 91-103 - [c111]Anna Lukina, Ashish Tiwari, Scott A. Smolka, Lukas Esterle, Junxing Yang, Radu Grosu:
Resilient Control and Safety for Cyber-Physical Systems. MT@CPSWeek 2018: 16-17 - [c110]Haris Isakovic, Denise Ratasich, Christian Hirsch, Michael Platzer, Bernhard Wally, Thomas Rausch, Dejan Nickovic, Willibald Krenn, Gerti Kappel, Schahram Dustdar, Radu Grosu:
CPS/IoT Ecosystem: A Platform for Research and Education. CyPhy/WESE 2018: 206-213 - [c109]Matt Schmittle, Anna Lukina, Lukas Vacek, Jnaneshwar Das, Christopher P. van Buskirk, Stephen A. Rees, Janos Sztipanovits, Radu Grosu, Vijay Kumar:
OpenUAV: a UAV testbed for the CPS and robotics community. ICCPS 2018: 130-139 - [c108]Anna Lukina, Arjun Kumar, Matt Schmittle, Abhijeet Singh, Jnaneshwar Das, Stephen A. Rees, Christopher P. van Buskirk, Janos Sztipanovits, Radu Grosu, Vijay Kumar:
Formation control and persistent monitoring in the openUAV swarm simulator on the NSF CPS-VO. ICCPS 2018: 353-354 - [c107]Guodong Wang, Mohamed Amin Ben Sassi, Radu Grosu:
A multi-bias recurrent neural network for modeling milling sensory data. ICPS 2018: 71-78 - [c106]Denise Ratasich, Thomas Preindl, Konstantin Selyunin, Radu Grosu:
Self-healing by property-guided structural adaptation. ICPS 2018: 199-205 - [c105]