Aditya V. Nori

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 45

Top Topics

Clinically Relevant

Language Processing

Brain Tumor Segmentation

Top Venues

BrainLes@MICCAI

Publications

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)
Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González
Cautionary Tales on Synthetic Controls in Survival Analyses. CLeaR (2024)
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 (2024)
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 (2024)
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 (2023)
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)
Javier González, Aditya V. Nori
Beyond Words: A Mathematical Framework for Interpreting Large Language Models. CoRR (2023)
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)
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 (2023)
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 (2023)
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 (2023)
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 (2023)
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)
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 (2023)
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)
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 (2022)
Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li
Repairing Neural Networks by Leaving the Right Past Behind. CoRR (2022)
Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li
Repairing Neural Networks by Leaving the Right Past Behind. NeurIPS (2022)
Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. 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 (2021)
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 (2021)
Ravi Mangal, Kartik Sarangmath, Aditya V. Nori, Alessandro Orso
Probabilistic Lipschitz Analysis of Neural Networks. SAS (2020)
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 (2020)
Ravi Mangal, Aditya V. Nori, Alessandro Orso
Robustness of Neural Networks: A Probabilistic and Practical Approach. CoRR (2019)
Saswat Padhi, Todd D. Millstein, Aditya V. Nori, Rahul Sharma
Overfitting in Synthesis: Theory and Practice. CAV (1) (2019)
Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori
Adaptive Neural Trees. ICML (2019)
Ravi Mangal, Aditya V. Nori, Alessandro Orso
Robustness of neural networks: a probabilistic and practical approach. ICSE (NIER) (2019)
Saswat Padhi, Todd D. Millstein, Aditya V. Nori, Rahul Sharma
Overfitting in Synthesis: Theory and Practice (Extended Version). CoRR (2019)
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori
Autofocus Layer for Semantic Segmentation. MICCAI (3) (2018)
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 (2018)
Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori
Adaptive Neural Trees. CoRR (2018)
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)
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori
Autofocus Layer for Semantic Segmentation. CoRR (2018)
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori
Quantifying Program Bias. CoRR (2017)
Loïc Le Folgoc, Aditya V. Nori, Antonio Criminisi
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes. IPMI (2017)
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)
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori
FairSquare: probabilistic verification of program fairness. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
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)
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya V. Nori, Antonio Criminisi
Measuring Neural Net Robustness with Constraints. NIPS (2016)
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya V. Nori
Fairness as a Program Property. CoRR (2016)
Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik
Query-guided maximum satisfiability. POPL (2016)
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya V. Nori, Antonio Criminisi
Measuring Neural Net Robustness with Constraints. CoRR (2016)
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 (2016)
Aleksandar Chakarov, Aditya V. Nori, Sriram K. Rajamani, Shayak Sen, Deepak Vijaykeerthy
Debugging Machine Learning Tasks. CoRR (2016)
Loïc Le Folgoc, Aditya V. Nori, Siddharth Ancha, Antonio Criminisi
Lifted Auto-Context Forests for Brain Tumour Segmentation. BrainLes@MICCAI (2016)
Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik
Scaling Relational Inference Using Proofs and Refutations. AAAI (2016)
Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy
Efficient synthesis of probabilistic programs. PLDI (2015)
He Zhu, Aditya V. Nori, Suresh Jagannathan
Dependent Array Type Inference from Tests. VMCAI (2015)
He Zhu, Aditya V. Nori, Suresh Jagannathan
Learning refinement types. ICFP (2015)
Venkatesh Vinayakarao, Rahul Purandare, Aditya V. Nori
Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources. PEPM (2015)
Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, Selva Samuel
A Provably Correct Sampler for Probabilistic Programs. FSTTCS (2015)
Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik
A user-guided approach to program analysis. ESEC/SIGSOFT FSE (2015)
Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. SAT (2015)
Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, Sriram K. Rajamani
Probabilistic programming. FOSE (2014)
Aditya V. Nori, Chung-Kil Hur, Sriram K. Rajamani, Selva Samuel
R2: An Efficient MCMC Sampler for Probabilistic Programs. AAAI (2014)
Rahul Sharma, Aditya V. Nori, Alex Aiken
Bias-variance tradeoffs in program analysis. POPL (2014)
Aditya V. Nori
Software reliability via machine learning (invited talk). FormaliSE (2014)
Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, Selva Samuel
Slicing probabilistic programs. PLDI (2014)
Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya V. Nori
MUX: algorithm selection for software model checkers. MSR (2014)
Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya V. Nori
A Data Driven Approach for Algebraic Loop Invariants. ESOP (2013)
Arun Tejasvi Chaganty, Aditya V. Nori, Sriram K. Rajamani
Efficiently Sampling Probabilistic Programs via Program Analysis. AISTATS (2013)
Aditya V. Nori, Rahul Sharma
Termination proofs from tests. ESEC/SIGSOFT FSE (2013)
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)
Rahul Kumar, Aditya V. Nori
The economics of static analysis tools. ESEC/SIGSOFT FSE (2013)
Guillaume Claret, Sriram K. Rajamani, Aditya V. Nori, Andrew D. Gordon, Johannes Borgström
Bayesian inference using data flow analysis. ESEC/SIGSOFT FSE (2013)
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya V. Nori
One-Bit Compressed Sensing: Provable Support and Vector Recovery. ICML (3) (2013)
Arun Tejasvi Chaganty, Akash Lal, Aditya V. Nori, Sriram K. Rajamani
Combining Relational Learning with SMT Solvers Using CEGAR. CAV (2013)
Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya V. Nori
Verification as Learning Geometric Concepts. SAS (2013)
Aditya V. Nori
Specification Inference and Invariant Generation: A Machine Learning Perspective. ATx/WInG@IJCAR (2012)
Aws Albarghouthi, Rahul Kumar, Aditya V. Nori, Sriram K. Rajamani
Parallelizing top-down interprocedural analyses. PLDI (2012)
Rahul Sharma, Aditya V. Nori, Alex Aiken
Interpolants as Classifiers. CAV (2012)
Aditya V. Nori, Sriram K. Rajamani
Program Analysis and Machine Learning: A Win-Win Deal. APLAS (2011)
Nels E. Beckman, Aditya V. Nori
Probabilistic, modular and scalable inference of typestate specifications. PLDI (2011)
Aditya V. Nori, Sriram K. Rajamani
Program Analysis and Machine Learning: A Win-Win Deal. SAS (2011)
Bhargav S. Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya V. Nori
Bottom-up shape analysis using LISF. ACM Trans. Program. Lang. Syst. 33 (5) (2011)
Bhargav S. Gulavani, Supratik Chakraborty, Aditya V. Nori, Sriram K. Rajamani
Refining abstract interpretations. Inf. Process. Lett. 110 (16) (2010)
Aditya V. Nori, Sriram K. Rajamani
An empirical study of optimizations in YOGI. ICSE (1) (2010)
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) (2010)
Patrice Godefroid, Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali
Compositional may-must program analysis: unleashing the power of alternation. POPL (2010)
William R. Harris, Akash Lal, Aditya V. Nori, Sriram K. Rajamani
Alternation for Termination. SAS (2010)
Aditya V. Nori, Sriram K. Rajamani
Verification, Testing and Statistics. TAP@TOOLS (2009)
Trishul M. Chilimbi, Ben Liblit, Krishna K. Mehra, Aditya V. Nori, Kapil Vaswani
HOLMES: Effective statistical debugging via efficient path profiling. ICSE (2009)
V. Benjamin Livshits, Aditya V. Nori, Sriram K. Rajamani, Anindya Banerjee
Merlin: specification inference for explicit information flow problems. PLDI (2009)
Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali, Aditya V. Thakur
The YogiProject: Software Property Checking via Static Analysis and Testing. TACAS (2009)
Bhargav S. Gulavani, Supratik Chakraborty, Ganesan Ramalingam, Aditya V. Nori
Bottom-Up Shape Analysis. SAS (2009)
Madhu Gopinathan, Aditya V. Nori, Sriram K. Rajamani
Combining Tests and Proofs. VSTTE (2008)
Nels E. Beckman, Aditya V. Nori, Sriram K. Rajamani, Robert J. Simmons
Proofs from tests. ISSTA (2008)
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) (2008)
Bhargav S. Gulavani, Supratik Chakraborty, Aditya V. Nori, Sriram K. Rajamani
Automatically Refining Abstract Interpretations. TACAS (2008)
Trishul M. Chilimbi, Aditya V. Nori, Kapil Vaswani
Quantifying the effectiveness of testing via efficient residual path profiling. ESEC/SIGSOFT FSE (2007)
Aditya V. Nori, Trishul M. Chilimbi, Kapil Vaswani
Quantifying the effectiveness of testing via efficient residual path profiling. ESEC/SIGSOFT FSE (Companion) (2007)
Kapil Vaswani, Aditya V. Nori, Trishul M. Chilimbi
Preferential path profiling: compactly numbering interesting paths. POPL (2007)
Aditya V. Nori, P. Shankar
Unifying Views of Tail-Biting Trellis Constructions for Linear Block Codes. IEEE Trans. Inf. Theory 52 (10) (2006)
Bhargav S. Gulavani, Thomas A. Henzinger, Yamini Kannan, Aditya V. Nori, Sriram K. Rajamani
SYNERGY: a new algorithm for property checking. SIGSOFT FSE (2006)
Helmut Seidl, Aditya V. Nori
On the Expressiveness of Tree Set Operators Universität Trier, Mathematik/Informatik, Forschungsbericht (2002)