Ramneet Kaur - RankMe

40 papers A* 3A 2B 1Journal 23Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Do Diffusion Models Dream of Electric Planes? Discrete and Continuous Simulation-Based Inference for Aircraft Design. CoRR Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb
2026	J	`jnl`	Optimal Abstractions for Verifying Properties of Kolmogorov-Arnold Networks (KANs). CoRR Noah Schwartz, Chandra Kanth Nagesh, Sriram Sankaranarayanan, Ramneet Kaur, Tuhin Sahai, Susmit Jha
2026	A*	`conf`	Privacy Preserving In-Context-Learning Framework for Large Language Models. AAAI Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha
2025	J	`jnl`	Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding. CoRR Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya, Anirban Roy, Colin Samplawski, Brian Matejek, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha
2025	J	`jnl`	Development of a cryptocurrency price prediction model: leveraging GRU and LSTM for Bitcoin, Litecoin and Ethereum. PeerJ Comput. Sci. Ramneet Kaur, Mudita Uppal, Deepali Gupta, Sapna Juneja, Syed Yasser Arafat, Junaid Rashid, Jungeun Kim, Roobaea Alroobaea
2025	A*	`conf`	Polysemantic Dropout: Conformal OOD Detection for Specialized LLMs. EMNLP Ayush Gupta, Ramneet Kaur, Anirban Roy, Adam D. Cobb, Rama Chellappa, Susmit Jha
2025	J	`jnl`	Polysemantic Dropout: Conformal OOD Detection for Specialized LLMs. CoRR Ayush Gupta, Ramneet Kaur, Anirban Roy, Adam D. Cobb, Rama Chellappa, Susmit Jha
2025	J	`jnl`	Privacy-Aware In-Context Learning for Large Language Models. CoRR Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha
2025	—	`ed.`	Proceedings of the 7th Workshop on Design Automation for CPS and IoT, DESTION 2025, Irvine, CA, USA, May 6-9, 2025 DESTION@CPSIoTWeek Susmit Jha, Ramneet Kaur, Fangqi Liu, Hyunjee Jin, Karthik Ramani, Arun Ramamurthy, Himanshu Neema
2025	—	`conf`	Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios. ICCPS Vivian Lin, Ramneet Kaur, Yahan Yang, Souradeep Dutta, Yiannis Kantaros, Anirban Roy, Susmit Jha, Oleg Sokolsky, Insup Lee
2025	J	`jnl`	Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios. CoRR Vivian Lin, Ramneet Kaur, Yahan Yang, Souradeep Dutta, Yiannis Kantaros, Anirban Roy, Susmit Jha, Oleg Sokolsky, Insup Lee
2025	A	`conf`	Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. UAI Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
2025	J	`jnl`	Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. CoRR Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
2025	—	`conf`	Taylor-Model Physics-Informed Neural Networks (PINNs) for Ordinary Differential Equations. NeuS Chandra Kanth Nagesh, Sriram Sankaranarayanan, Ramneet Kaur, Tuhin Sahai, Susmit Jha
2025	J	`jnl`	Taylor-Model Physics-Informed Neural Networks (PINNs) for Ordinary Differential Equations. CoRR Chandra Kanth Nagesh, Sriram Sankaranarayanan, Ramneet Kaur, Tuhin Sahai, Susmit Jha
2025	A	`conf`	Zero-Shot Detection of Out-of-Context Objects Using Foundation Models. WACV Anirban Roy, Adam D. Cobb, Ramneet Kaur, Sumit Jha, Nathaniel D. Bastian, Alexander M. Berenbeim, Robert H. Thomson, Iain Cruickshank, Alvaro Velasquez, Susmit Jha
2024	J	`jnl`	Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI. CoRR Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M. Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha
2024	B	`conf`	Automating Weak Label Generation for Data Programming with Clinicians in the Loop. CHASE Jean Park, Sydney Pugh, Kaustubh Sridhar, Mengyu Liu, Navish Yarna, Ramneet Kaur, Souradeep Dutta, Elena Bernardis, Oleg Sokolsky, Insup Lee
2024	J	`jnl`	Automating Weak Label Generation for Data Programming with Clinicians in the Loop. CoRR Jean Park, Sydney Pugh, Kaustubh Sridhar, Mengyu Liu, Navish Yarna, Ramneet Kaur, Souradeep Dutta, Elena Bernardis, Oleg Sokolsky, Insup Lee
2024	J	`jnl`	Memory-based Distribution Shift Detection for Learning Enabled Cyber-Physical Systems with Statistical Guarantees. ACM Trans. Cyber Phys. Syst. Yahan Yang, Ramneet Kaur, Souradeep Dutta, Insup Lee
2024	J	`jnl`	Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal Guarantees. ACM Trans. Cyber Phys. Syst. Ramneet Kaur, Yahan Yang, Oleg Sokolsky, Insup Lee
2024	—	`conf`	Post-hoc Uncertainty Quantification for Neurosymbolic Artificial Intelligence. MILCOM Alexander M. Berenbeim, Ramneet Kaur, Adam D. Cobb, Anirban Roy, Susmit Jha, Nathaniel D. Bastian
2023	—	`conf`	Automated Labeling Function Generation using Distance Functions for Physiological Alarm Suppression. ICCPS Sydney Pugh, Souradeep Dutta, Ramneet Kaur, Yahan Yang, Elena Bernardis, Insup Lee
2023	—	`conf`	CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems. ICCPS Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Yahan Yang, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee
2023	J	`jnl`	Detection of Adversarial Physical Attacks in Time-Series Image Data. CoRR Ramneet Kaur, Yiannis Kantaros, Wenwen Si, James Weimer, Insup Lee
2023	J	`jnl`	Learner-Centric Hybrid Filtering-Based Recommender System for Massive Open Online Courses. Int. J. Perform. Eng. Ramneet Kaur, Deepali Gupta, Mani Madhukar
2023	—	`conf`	Predicting Out-of-Distribution Performance of Deep Neural Networks Using Model Conformance. ICAA Ramneet Kaur, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee
2023	J	`jnl`	Using Semantic Information for Defining and Detecting OOD Inputs. CoRR Ramneet Kaur, Xiayan Ji, Souradeep Dutta, Michele Caprio, Yahan Yang, Elena Bernardis, Oleg Sokolsky, Insup Lee
2022	J	`jnl`	CODiT: Conformal Out-of-Distribution Detection in Time-Series Data. CoRR Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee
2022	—	`conf`	Interpretable Detection of Distribution Shifts in Learning Enabled Cyber-Physical Systems. ICCPS Yahan Yang, Ramneet Kaur, Souradeep Dutta, Insup Lee
2022	J	`jnl`	Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations. CoRR Kaustubh Sridhar, Souradeep Dutta, Ramneet Kaur, James Weimer, Oleg Sokolsky, Insup Lee
2022	A*	`conf`	iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection. AAAI Ramneet Kaur, Susmit Jha, Anirban Roy, Sangdon Park, Edgar Dobriban, Oleg Sokolsky, Insup Lee
2022	J	`jnl`	iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection. CoRR Ramneet Kaur, Susmit Jha, Anirban Roy, Sangdon Park, Edgar Dobriban, Oleg Sokolsky, Insup Lee
2021	J	`jnl`	Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs. CoRR Ramneet Kaur, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee
2021	J	`jnl`	Detecting OODs as datapoints with High Uncertainty. CoRR Ramneet Kaur, Susmit Jha, Anirban Roy, Sangdon Park, Oleg Sokolsky, Insup Lee
2020	—	`conf`	Assurance Case Patterns for Cyber-Physical Systems with Deep Neural Networks. SAFECOMP Workshops Ramneet Kaur, Radoslav Ivanov, Matthew Cleaveland, Oleg Sokolsky, Insup Lee
2019	—	`conf`	Runtime Verification of Parametric Properties Using SMEDL. From Reactive Systems to Cyber-Physical Systems Teng Zhang, Ramneet Kaur, Insup Lee, Oleg Sokolsky
2018	—	`conf`	Parameter Invariant Monitoring for Signal Temporal Logic. HSCC Nima Roohi, Ramneet Kaur, James Weimer, Oleg Sokolsky, Insup Lee
2018	J	`jnl`	Self-Driving Vehicle Verification Towards a Benchmark. CoRR Nima Roohi, Ramneet Kaur, James Weimer, Oleg Sokolsky, Insup Lee
2013	J	`jnl`	Design and Implementation of Car Parking System on FPGA. CoRR Ramneet Kaur, Balwinder Singh