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ORCIDRajarshi Roy 0002
Person information
- affiliation: University of Oxford, UK
- affiliation (former): Max Planck Institute for Software Systems, Kaiserslautern, Germany
- affiliation (former): Chennai Mathematical Institute, Chennai, India
- affiliation (PhD 2024): Kaiserslautern University of Technology, Germany
Other persons with the same name
- Rajarshi Roy
- Rajarshi Roy 0001
![[0000-0001-9474-0031]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-9474-0031")
— Indian Institute of Technology Kharagpur, India - Rajarshi Roy 0003 — Nvidia,Santa Clara, CA, USA
- Rajarshi Roy 0004 — University of Maryland, College Park, MD, USA (and 1 more)
- Rajarshi Roy 0005 — Corvid Technologies, Mooresville, NC, USA (and 2 more)
- Rajarshi Roy 0006 — Indian Institute of Technology Indore, Department of Biosciences and Biomedical Engineering, India
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2020 – today
- 2025
[c18]Benjamin Bordais, Daniel Neider, Rajarshi Roy:
The Complexity of Learning LTL, CTL and ATL Formulas. STACS 2025: 19:1-19:20- [i16]Daniel Neider, Rajarshi Roy:
What is Formal Verification without Specifications? A Survey on mining LTL Specifications. CoRR abs/2501.16274 (2025) - 2024
- [b1]Rajarshi Roy:
Learning Temporal Properties for Explainability and Verification. Kaiserslautern University of Technology, Germany, 2024 - [j4]Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow, Daniel Neider:
Scarlet: Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic. J. Open Source Softw. 9(93): 5052 (2024) - [j3]Lina Ye, Igor Khmelnitsky, Serge Haddad, Benoît Barbot, Benedikt Bollig, Martin Leucker, Daniel Neider, Rajarshi Roy:
Analyzing Robustness of Angluin's L$^*$ Algorithm in Presence of Noise. Log. Methods Comput. Sci. 20(1) (2024) - [c17]Daniel Neider, Rajarshi Roy:
What Is Formal Verification Without Specifications? A Survey on Mining LTL Specifications. Principles of Verification (3) 2024: 109-125 - [c16]Benjamin Bordais, Daniel Neider, Rajarshi Roy:
Learning Branching-Time Properties in CTL and ATL via Constraint Solving. FM (1) 2024: 304-323 - [c15]Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow, Daniel Neider, Guillermo A. Pérez:
Synthesizing Efficiently Monitorable Formulas in Metric Temporal Logic. VMCAI (2) 2024: 264-288 - [i15]Benjamin Bordais, Daniel Neider, Rajarshi Roy:
Learning Branching-Time Properties in CTL and ATL via Constraint Solving. CoRR abs/2406.19890 (2024) - [i14]Benjamin Bordais, Daniel Neider, Rajarshi Roy:
The Complexity of Learning Temporal Properties. CoRR abs/2408.04486 (2024) - 2023
- [j2]Igor Khmelnitsky, Daniel Neider, Rajarshi Roy, Xuan Xie, Benoît Barbot, Benedikt Bollig, Alain Finkel, Serge Haddad, Martin Leucker, Lina Ye:
Analysis of recurrent neural networks via property-directed verification of surrogate models. Int. J. Softw. Tools Technol. Transf. 25(3): 341-354 (2023) - [c14]Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu:
Learning Interpretable Temporal Properties from Positive Examples Only. AAAI 2023: 6507-6515 - [c13]Simon Lutz, Daniel Neider, Rajarshi Roy:
Specification Sketching for Linear Temporal Logic. ATVA 2023: 26-48 - [c12]Yash Paliwal, Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Xiaoming Duan, Ufuk Topcu, Zhe Xu:
Reinforcement Learning with Temporal-Logic-Based Causal Diagrams. CD-MAKE 2023: 123-140 - [i13]Lina Ye, Igor Khmelnitsky, Serge Haddad, Benoît Barbot, Benedikt Bollig, Martin Leucker, Daniel Neider, Rajarshi Roy:
Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise. CoRR abs/2306.08266 (2023) - [i12]Yash Paliwal, Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Xiaoming Duan, Ufuk Topcu, Zhe Xu:
Reinforcement Learning with Temporal-Logic-Based Causal Diagrams. CoRR abs/2306.13732 (2023) - [i11]Rajarshi Roy, Daniel Neider:
Inferring Properties in Computation Tree Logic. CoRR abs/2310.13778 (2023) - [i10]Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow, Daniel Neider, Guillermo A. Pérez:
Synthesizing Efficiently Monitorable Formulas in Metric Temporal Logic. CoRR abs/2310.17410 (2023) - [i9]Benjamin Bordais, Daniel Neider, Rajarshi Roy:
Learning Temporal Properties is NP-hard. CoRR abs/2312.11403 (2023) - 2022
- [j1]Jean-Raphaël Gaglione, Daniel Neider, Rajarshi Roy, Ufuk Topcu, Zhe Xu:
MaxSAT-based temporal logic inference from noisy data. Innov. Syst. Softw. Eng. 18(3): 427-442 (2022) - [c11]Satya Prakash Nayak, Daniel Neider, Rajarshi Roy, Martin Zimmermann:
Robust Computation Tree Logic. NFM 2022: 538-556 - [c10]Daniel Neider, Rajarshi Roy:
Expanding the Horizon of Linear Temporal Logic Inference for Explainability. RE Workshops 2022: 103-107 - [c9]Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow, Daniel Neider:
Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic. TACAS (1) 2022: 263-280 - [c8]Igor Khmelnitsky, Serge Haddad, Lina Ye, Benoît Barbot, Benedikt Bollig, Martin Leucker, Daniel Neider, Rajarshi Roy:
Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise. GandALF 2022: 81-96 - [i8]Satya Prakash Nayak, Daniel Neider, Rajarshi Roy, Martin Zimmermann:
Robust Computation Tree Logic. CoRR abs/2201.07116 (2022) - [i7]Simon Lutz, Daniel Neider, Rajarshi Roy:
Specification sketching for Linear Temporal Logic. CoRR abs/2206.06722 (2022) - [i6]Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu:
Learning Interpretable Temporal Properties from Positive Examples Only. CoRR abs/2209.02650 (2022) - [i5]Jean-Raphaël Gaglione, Rajarshi Roy, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu:
Learning Temporal Logic Properties: an Overview of Two Recent Methods. CoRR abs/2212.00916 (2022) - 2021
- [c7]Jean-Raphaël Gaglione, Daniel Neider, Rajarshi Roy, Ufuk Topcu, Zhe Xu:
Learning Linear Temporal Properties from Noisy Data: A MaxSAT-Based Approach. ATVA 2021: 74-90 - [c6]Igor Khmelnitsky, Daniel Neider, Rajarshi Roy, Xuan Xie, Benoît Barbot, Benedikt Bollig, Alain Finkel, Serge Haddad, Martin Leucker, Lina Ye:
Property-Directed Verification and Robustness Certification of Recurrent Neural Networks. ATVA 2021: 364-380 - [c5]Benedikt Böing, Rajarshi Roy, Daniel Neider, Emmanuel Müller:
QUGA - Quality Guarantees for Autoencoders. OVERLAY@GandALF 2021: 103-107 - [c4]Benoît Barbot, Benedikt Bollig, Alain Finkel, Serge Haddad, Igor Khmelnitsky, Martin Leucker, Daniel Neider, Rajarshi Roy, Lina Ye:
Extracting Context-Free Grammars from Recurrent Neural Networks using Tree-Automata Learning and A* Search. ICGI 2021: 113-129 - [i4]Jean-Raphaël Gaglione, Daniel Neider, Rajarshi Roy, Ufuk Topcu, Zhe Xu:
Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach. CoRR abs/2104.15083 (2021) - [i3]Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow, Daniel Neider:
Scalable Anytime Algorithms for Learning Formulas in Linear Temporal Logic. CoRR abs/2110.06726 (2021) - 2020
- [c3]Rajarshi Roy, Dana Fisman, Daniel Neider:
Learning Interpretable Models in the Property Specification Language. IJCAI 2020: 2213-2219 - [c2]Benedikt Böing, Rajarshi Roy, Emmanuel Müller, Daniel Neider:
Quality Guarantees for Autoencoders via Unsupervised Adversarial Attacks. ECML/PKDD (2) 2020: 206-222 - [i2]Rajarshi Roy, Dana Fisman, Daniel Neider:
Learning Interpretable Models in the Property Specification Language. CoRR abs/2002.03668 (2020) - [i1]Igor Khmelnitsky, Daniel Neider, Rajarshi Roy, Benoît Barbot, Benedikt Bollig, Alain Finkel, Serge Haddad, Martin Leucker, Lina Ye:
Property-Directed Verification of Recurrent Neural Networks. CoRR abs/2009.10610 (2020)
2010 – 2019
- 2018
- [c1]Ahmed Bouajjani, Constantin Enea, Madhavan Mukund, Rajarshi Roy:
On Verifying TSO Robustness for Event-Driven Asynchronous Programs. NETYS 2018: 225-239
Coauthor Index
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