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ORCIDAditya V. Nori
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- affiliation: Microsoft Research, Cambridge, UK
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2020 – today
- 2023
[c59]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- [c58]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 - [i18]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) - [i17]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) - 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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