Aditya V. Nori
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
53
Venues
25
Active years
2007–2025
Best venue rank
A*
Where they publish
- A*ICML5 papers
- BSAS5 papers
- A*ICSE5 papers
- A*POPL5 papers
- A*PLDI5 papers
- A*CAV3 papers
- AMICCAI3 papers
- A*CHI2 papers
- A*ECCV2 papers
- A*AAAI2 papers
- ATACAS2 papers
- A*ICLR1 paper
- A*CVPR1 paper
- A*EMNLP1 paper
- AICFP1 paper
- CPEPM1 paper
- ASAT1 paper
- BVMCAI1 paper
- AMSR1 paper
- AAISTATS1 paper
- AESOP1 paper
- ACADE1 paper
- BAPLAS1 paper
- CTAP1 paper
- AISSTA1 paper
Papers
53 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Reasoning Elicitation in Language Models via Counterfactual Feedback. | Alihan Hyk, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier Gonzlez |
| 2025 | ICML | Compositional Causal Reasoning Evaluation in Language Models. | Jacqueline R. M. A. Maasch, Alihan Hyk, Xinnuo Xu, Aditya V. Nori, Javier Gonzlez |
| 2025 | ICML | RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation. | Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Risa Ueno, Fabian Falck, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzlez |
| 2024 | CHI | Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. | 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 Prez-Garca, Harshita Sharma, Ozan Oktay, Matthew P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme |
| 2024 | ECCV | RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing. | Fernando Prez-Garca, 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 |
| 2023 | CHI | Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward. | Anja Thieme, Aditya V. Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger |
| 2023 | CVPR | Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. | Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Prez-Garca, 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 |
| 2023 | EMNLP | Exploring the Boundaries of GPT-4 in Radiology. | Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Wetscherek, Robert Tinn, Harshita Sharma, Fernando Prez-Garca, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle |
| 2022 | ECCV | Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. | 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 |
| 2020 | SAS | Probabilistic Lipschitz Analysis of Neural Networks. | Ravi Mangal, Kartik Sarangmath, Aditya V. Nori, Alessandro Orso |
| 2019 | CAV | Overfitting in Synthesis: Theory and Practice. | Saswat Padhi, Todd D. Millstein, Aditya V. Nori, Rahul Sharma |
| 2019 | ICML | Adaptive Neural Trees. | Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori |
| 2019 | ICSE | Robustness of neural networks: a probabilistic and practical approach. | Ravi Mangal, Aditya V. Nori, Alessandro Orso |
| 2018 | ICML | Semi-Supervised Learning via Compact Latent Space Clustering. | Konstantinos Kamnitsas, Daniel Coelho de Castro, Loc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori |
| 2018 | MICCAI | Autofocus Layer for Semantic Segmentation. | Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori |
| 2016 | AAAI | Scaling Relational Inference Using Proofs and Refutations. | Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik |
| 2016 | MICCAI | Lifted Auto-Context Forests for Brain Tumour Segmentation. | Loc Le Folgoc, Aditya V. Nori, Siddharth Ancha, Antonio Criminisi |
| 2016 | MICCAI | DeepMedic for Brain Tumor Segmentation. | Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker |
| 2016 | POPL | Query-guided maximum satisfiability. | Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik |
| 2015 | ICFP | Learning refinement types. | He Zhu, Aditya V. Nori, Suresh Jagannathan |
| 2015 | PEPM | Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources. | Venkatesh Vinayakarao, Rahul Purandare, Aditya V. Nori |
| 2015 | PLDI | Efficient synthesis of probabilistic programs. | Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy |
| 2015 | SAT | Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. | Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik |
| 2015 | VMCAI | Dependent Array Type Inference from Tests. | He Zhu, Aditya V. Nori, Suresh Jagannathan |
| 2014 | AAAI | R2: An Efficient MCMC Sampler for Probabilistic Programs. | Aditya V. Nori, Chung-Kil Hur, Sriram K. Rajamani, Selva Samuel |
| 2014 | ICSE | Probabilistic programming. | Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, Sriram K. Rajamani |
| 2014 | ICSE | Software reliability via machine learning (invited talk). | Aditya V. Nori |
| 2014 | MSR | MUX: algorithm selection for software model checkers. | Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya V. Nori |
| 2014 | PLDI | Slicing probabilistic programs. | Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, Selva Samuel |
| 2014 | POPL | Bias-variance tradeoffs in program analysis. | Rahul Sharma, Aditya V. Nori, Alex Aiken |
| 2013 | AISTATS | Efficiently Sampling Probabilistic Programs via Program Analysis. | Arun Tejasvi Chaganty, Aditya V. Nori, Sriram K. Rajamani |
| 2013 | CAV | Combining Relational Learning with SMT Solvers Using CEGAR. | Arun Tejasvi Chaganty, Akash Lal, Aditya V. Nori, Sriram K. Rajamani |
| 2013 | ESOP | A Data Driven Approach for Algebraic Loop Invariants. | Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya V. Nori |
| 2013 | ICML | One-Bit Compressed Sensing: Provable Support and Vector Recovery. | Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya V. Nori |
| 2013 | POPL | A model-learner pattern for bayesian reasoning. | Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgstrm, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, Claudio V. Russo |
| 2013 | SAS | Verification as Learning Geometric Concepts. | Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya V. Nori |
| 2012 | CADE | Specification Inference and Invariant Generation: A Machine Learning Perspective. | Aditya V. Nori |
| 2012 | CAV | Interpolants as Classifiers. | Rahul Sharma, Aditya V. Nori, Alex Aiken |
| 2012 | PLDI | Parallelizing top-down interprocedural analyses. | Aws Albarghouthi, Rahul Kumar, Aditya V. Nori, Sriram K. Rajamani |
| 2011 | APLAS | Program Analysis and Machine Learning: A Win-Win Deal. | Aditya V. Nori, Sriram K. Rajamani |
| 2011 | PLDI | Probabilistic, modular and scalable inference of typestate specifications. | Nels E. Beckman, Aditya V. Nori |
| 2011 | SAS | Program Analysis and Machine Learning: A Win-Win Deal. | Aditya V. Nori, Sriram K. Rajamani |
| 2010 | ICSE | An empirical study of optimizations in YOGI. | Aditya V. Nori, Sriram K. Rajamani |
| 2010 | POPL | Compositional may-must program analysis: unleashing the power of alternation. | Patrice Godefroid, Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali |
| 2010 | SAS | Alternation for Termination. | William R. Harris, Akash Lal, Aditya V. Nori, Sriram K. Rajamani |
| 2009 | ICSE | HOLMES: Effective statistical debugging via efficient path profiling. | Trishul M. Chilimbi, Ben Liblit, Krishna K. Mehra, Aditya V. Nori, Kapil Vaswani |
| 2009 | PLDI | Merlin: specification inference for explicit information flow problems. | V. Benjamin Livshits, Aditya V. Nori, Sriram K. Rajamani, Anindya Banerjee |
| 2009 | SAS | Bottom-Up Shape Analysis. | Bhargav S. Gulavani, Supratik Chakraborty, Ganesan Ramalingam, Aditya V. Nori |
| 2009 | TACAS | The YogiProject: Software Property Checking via Static Analysis and Testing. | Aditya V. Nori, Sriram K. Rajamani, SaiDeep Tetali, Aditya V. Thakur |
| 2009 | TAP | Verification, Testing and Statistics. | Aditya V. Nori, Sriram K. Rajamani |
| 2008 | ISSTA | Proofs from tests. | Nels E. Beckman, Aditya V. Nori, Sriram K. Rajamani, Robert J. Simmons |
| 2008 | TACAS | Automatically Refining Abstract Interpretations. | Bhargav S. Gulavani, Supratik Chakraborty, Aditya V. Nori, Sriram K. Rajamani |
| 2007 | POPL | Preferential path profiling: compactly numbering interesting paths. | Kapil Vaswani, Aditya V. Nori, Trishul M. Chilimbi |