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ORCIDAditya V. Nori
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- affiliation: Microsoft Research, Cambridge, UK
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2020 – today
- 2024
[c62]Nur Yildirim
, Hannah Richardson, Maria Teodora Wetscherek, Junaid Bajwa, Joseph Jacob, Mark Ames Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie L. Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CHI 2024: 444:1-444:22- [c61]Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González:
Cautionary Tales on Synthetic Controls in Survival Analyses. CLeaR 2024: 143-159 - [i25]Nur Yildirim, Hannah Richardson, Maria T. A. Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A. Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie L. Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CoRR abs/2402.14252 (2024) - [i24]Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson, Fernando Pérez-García, Stephanie L. Hyland, Shruthi Bannur, Daniel C. Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya V. Nori, Stephen Harris, Joseph Jacob:
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. CoRR abs/2405.05299 (2024) - [i23]Javier González, Aditya V. Nori:
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models. CoRR abs/2408.08210 (2024) - 2023
- [j7]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Trans. Assoc. Comput. Linguistics 11: 1097-1113 (2023) - [c60]Anja Thieme, Aditya V. Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger:
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward. CHI Extended Abstracts 2023: 512:1-512:4 - [c59]Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CVPR 2023: 15016-15027 - [c58]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. EMNLP 2023: 14414-14445 - [i22]Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CoRR abs/2301.04558 (2023) - [i21]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. CoRR abs/2303.13386 (2023) - [i20]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. CoRR abs/2310.14573 (2023) - [i19]Javier González Hernández, Cliff Wong, Zelalem Gero, Jass Bagga, Risa Ueno, Isabel Chien, Eduard Oravkin, Emre Kiciman, Aditya V. Nori, Roshanthi Weerasinghe, Rom S. Leidner, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models. CoRR abs/2311.01301 (2023) - [i18]Javier González, Aditya V. Nori:
Beyond Words: A Mathematical Framework for Interpreting Large Language Models. CoRR abs/2311.03033 (2023) - [i17]Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel C. Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse:
RadEdit: stress-testing biomedical vision models via diffusion image editing. CoRR abs/2312.12865 (2023) - 2022
- [c57]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 2022: 1-21 - [c56]Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li:
Repairing Neural Networks by Leaving the Right Past Behind. NeurIPS 2022 - [i16]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR abs/2204.09817 (2022) - [i15]Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li:
Repairing Neural Networks by Leaving the Right Past Behind. CoRR abs/2207.04806 (2022) - 2021
- [i14]Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya V. Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel C. Castro:
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs. CoRR abs/2107.06618 (2021) - [i13]Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem Can Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya V. Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay:
Active label cleaning: Improving dataset quality under resource constraints. CoRR abs/2109.00574 (2021) - 2020
- [c55]Ravi Mangal, Kartik Sarangmath, Aditya V. Nori, Alessandro Orso:
Probabilistic Lipschitz Analysis of Neural Networks. SAS 2020: 274-309 - [i12]Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya V. Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare:
Secure Medical Image Analysis with CrypTFlow. CoRR abs/2012.05064 (2020)
2010 – 2019
- 2019
- [c54]Saswat Padhi, Todd D. Millstein, Aditya V. Nori, Rahul Sharma:
Overfitting in Synthesis: Theory and Practice. CAV (1) 2019: 315-334 - [c53]Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori:
Adaptive Neural Trees. ICML 2019: 6166-6175 - [c52]Ravi Mangal, Aditya V. Nori, Alessandro Orso:
Robustness of neural networks: a probabilistic and practical approach. ICSE (NIER) 2019: 93-96 - [i11]Ravi Mangal, Aditya V. Nori, Alessandro Orso:
Robustness of Neural Networks: A Probabilistic and Practical Approach. CoRR abs/1902.05983 (2019) - [i10]Saswat Padhi, Todd D. Millstein, Aditya V. Nori, Rahul Sharma:
Overfitting in Synthesis: Theory and Practice (Extended Version). CoRR abs/1905.07457 (2019) - 2018
- [c51]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. ICML 2018: 2464-2473 - [c50]Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori:
Autofocus Layer for Semantic Segmentation. MICCAI (3) 2018: 603-611 - [i9]Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori:
Autofocus Layer for Semantic Segmentation. CoRR abs/1805.08403 (2018) - [i8]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. CoRR abs/1806.02679 (2018) - [i7]Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori:
Adaptive Neural Trees. CoRR abs/1807.06699 (2018) - 2017
- [j6]Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori:
FairSquare: probabilistic verification of program fairness. Proc. ACM Program. Lang. 1(OOPSLA): 80:1-80:30 (2017) - [c49]Loïc Le Folgoc, Aditya V. Nori, Antonio Criminisi:
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes. IPMI 2017: 67-79 - [c48]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. IPMI 2017: 597-609 - [i6]Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori:
Quantifying Program Bias. CoRR abs/1702.05437 (2017) - 2016
- [c47]Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik:
Scaling Relational Inference Using Proofs and Refutations. AAAI 2016: 3278-3286 - [c46]Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
DeepMedic for Brain Tumor Segmentation. BrainLes@MICCAI 2016: 138-149 - [c45]Loïc Le Folgoc, Aditya V. Nori, Siddharth Ancha, Antonio Criminisi:
Lifted Auto-Context Forests for Brain Tumour Segmentation. BrainLes@MICCAI 2016: 171-183 - [c44]Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya V. Nori, Antonio Criminisi:
Measuring Neural Net Robustness with Constraints. NIPS 2016: 2613-2621 - [c43]Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik:
Query-guided maximum satisfiability. POPL 2016: 109-122 - [i5]Aleksandar Chakarov, Aditya V. Nori, Sriram K. Rajamani, Shayak Sen, Deepak Vijaykeerthy:
Debugging Machine Learning Tasks. CoRR abs/1603.07292 (2016) - [i4]Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya V. Nori, Antonio Criminisi:
Measuring Neural Net Robustness with Constraints. CoRR abs/1605.07262 (2016) - [i3]Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori:
Fairness as a Program Property. CoRR abs/1610.06067 (2016) - [i2]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks. CoRR abs/1612.08894 (2016) - 2015
- [c42]Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, Selva Samuel:
A Provably Correct Sampler for Probabilistic Programs. FSTTCS 2015: 475-488 - [c41]He Zhu, Aditya V. Nori, Suresh Jagannathan:
Learning refinement types. ICFP 2015: 400-411 - [c40]Venkatesh Vinayakarao, Rahul Purandare, Aditya V. Nori:
Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources. PEPM 2015: 21-26 - [c39]Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy:
Efficient synthesis of probabilistic programs. PLDI 2015: 208-217 - [c38]Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik:
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. SAT 2015: 299-306 - [c37]Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik:
A user-guided approach to program analysis. ESEC/SIGSOFT FSE 2015: 462-473 - [c36]He Zhu, Aditya V. Nori, Suresh Jagannathan:
Dependent Array Type Inference from Tests. VMCAI 2015: 412-430 - 2014
- [c35]Aditya V. Nori, Chung-Kil Hur, Sriram K. Rajamani, Selva Samuel:
R2: An Efficient MCMC Sampler for Probabilistic Programs. AAAI 2014: 2476-2482 - [c34]Aditya V. Nori:
Software reliability via machine learning (invited talk). FormaliSE 2014: 1-2 - [c33]Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, Sriram K. Rajamani:
Probabilistic programming. FOSE 2014: 167-181 - [c32]Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya V. Nori:
MUX: algorithm selection for software model checkers. MSR 2014: 132-141 - [c31]Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, Selva Samuel:
Slicing probabilistic programs. PLDI 2014: 133-144 - [c30]Rahul Sharma, Aditya V. Nori, Alex Aiken:
Bias-variance tradeoffs in program analysis. POPL 2014: 127-138 - 2013
- [c29]Arun Tejasvi Chaganty, Aditya V. Nori, Sriram K. Rajamani:
Efficiently Sampling Probabilistic Programs via Program Analysis. AISTATS 2013: 153-160 - [c28]Arun Tejasvi Chaganty, Akash Lal, Aditya V. Nori, Sriram K. Rajamani:
Combining Relational Learning with SMT Solvers Using CEGAR. CAV 2013: 447-462 - [c27]Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya V. Nori:
A Data Driven Approach for Algebraic Loop Invariants. ESOP 2013: 574-592 - [c26]Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya V. Nori:
One-Bit Compressed Sensing: Provable Support and Vector Recovery. ICML (3) 2013: 154-162 - [c25]Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgström, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, Claudio V. Russo:
A model-learner pattern for bayesian reasoning. POPL 2013: 403-416 - [c24]Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya V. Nori:
Verification as Learning Geometric Concepts. SAS 2013: 388-411 - [c23]Guillaume Claret, Sriram K. Rajamani, Aditya V. Nori, Andrew D. Gordon, Johannes Borgström:
Bayesian inference using data flow analysis. ESEC/SIGSOFT FSE 2013: 92-102 - [c22]Aditya V. Nori, Rahul Sharma:
Termination proofs from tests. ESEC/SIGSOFT FSE 2013: 246-256 - [c21]Rahul Kumar, Aditya V. Nori:
The economics of static analysis tools. ESEC/SIGSOFT FSE 2013: 707-710 - 2012
- [c20]Aditya V. Nori:
Specification Inference and Invariant Generation: A Machine Learning Perspective. ATx/WInG@IJCAR 2012: 54 - [c19]Rahul Sharma, Aditya V. Nori, Alex Aiken:
Interpolants as Classifiers. CAV 2012: 71-87 - [c18]Aws Albarghouthi, Rahul Kumar, Aditya V. Nori, Sriram K. Rajamani:
Parallelizing top-down interprocedural analyses. PLDI 2012: 217-228 - 2011
- [j5]Bhargav S. Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya V. Nori:
Bottom-up shape analysis using LISF. ACM Trans. Program. Lang. Syst. 33(5): 17:1-17:41 (2011) - [c17]Aditya V. Nori, Sriram K. Rajamani:
Program Analysis and Machine Learning: A Win-Win Deal. APLAS 2011: 1-2 - [c16]Nels E. Beckman, Aditya V. Nori:
Probabilistic, modular and scalable inference of typestate specifications. PLDI 2011: 211-221 - [c15]Aditya V. Nori, Sriram K. Rajamani:
Program Analysis and Machine Learning: A Win-Win Deal. SAS 2011: 2-3 - 2010
- [j4]Bhargav S. Gulavani, Supratik Chakraborty, Aditya V. Nori, Sriram K. Rajamani:
Refining abstract interpretations. Inf. Process. Lett. 110(16): 666-671 (2010) - [j3]Nels E. Beckman, Aditya V. Nori, Sriram K. Rajamani, Robert J. Simmons, SaiDeep Tetali, Aditya V. Thakur:
Proofs from Tests. IEEE Trans. Software Eng. 36(4): 495-508 (2010) - [c14]Aditya V. Nori, Sriram K. Rajamani:
An empirical study of optimizations in YOGI. ICSE (1) 2010: 355-364 - [c13]Patrice Godefroid, Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali:
Compositional may-must program analysis: unleashing the power of alternation. POPL 2010: 43-56 - [c12]William R. Harris, Akash Lal, Aditya V. Nori, Sriram K. Rajamani:
Alternation for Termination. SAS 2010: 304-319
2000 – 2009
- 2009
- [c11]Trishul M. Chilimbi, Ben Liblit, Krishna K. Mehra, Aditya V. Nori, Kapil Vaswani:
HOLMES: Effective statistical debugging via efficient path profiling. ICSE 2009: 34-44 - [c10]V. Benjamin Livshits, Aditya V. Nori, Sriram K. Rajamani, Anindya Banerjee:
Merlin: specification inference for explicit information flow problems. PLDI 2009: 75-86 - [c9]Bhargav S. Gulavani, Supratik Chakraborty, Ganesan Ramalingam, Aditya V. Nori:
Bottom-Up Shape Analysis. SAS 2009: 188-204 - [c8]Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali, Aditya V. Thakur:
The YogiProject: Software Property Checking via Static Analysis and Testing. TACAS 2009: 178-181 - [c7]Aditya V. Nori, Sriram K. Rajamani:
Verification, Testing and Statistics. TAP@TOOLS 2009: 6-9 - 2008
- [j2]Patrice Godefroid, Jonathan de Halleux, Aditya V. Nori, Sriram K. Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin:
Automating Software Testing Using Program Analysis. IEEE Softw. 25(5): 30-37 (2008) - [c6]Nels E. Beckman, Aditya V. Nori, Sriram K. Rajamani, Robert J. Simmons:
Proofs from tests. ISSTA 2008: 3-14 - [c5]Bhargav S. Gulavani, Supratik Chakraborty, Aditya V. Nori, Sriram K. Rajamani:
Automatically Refining Abstract Interpretations. TACAS 2008: 443-458 - [c4]Madhu Gopinathan, Aditya V. Nori, Sriram K. Rajamani:
Combining Tests and Proofs. VSTTE 2008: 4-5 - 2007
- [c3]Kapil Vaswani, Aditya V. Nori, Trishul M. Chilimbi:
Preferential path profiling: compactly numbering interesting paths. POPL 2007: 351-362 - [c2]Trishul M. Chilimbi, Aditya V. Nori, Kapil Vaswani:
Quantifying the effectiveness of testing via efficient residual path profiling. ESEC/SIGSOFT FSE 2007: 545-548 - 2006
- [j1]Aditya V. Nori, P. Shankar:
Unifying Views of Tail-Biting Trellis Constructions for Linear Block Codes. IEEE Trans. Inf. Theory 52(10): 4431-4443 (2006) - [c1]Bhargav S. Gulavani, Thomas A. Henzinger, Yamini Kannan, Aditya V. Nori, Sriram K. Rajamani:
SYNERGY: a new algorithm for property checking. SIGSOFT FSE 2006: 117-127 - 2002
- [i1]Helmut Seidl, Aditya V. Nori:
On the Expressiveness of Tree Set Operators. Universität Trier, Mathematik/Informatik, Forschungsbericht 02-17 (2002)
Coauthor Index
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