Ranganath Krishnan

33 papers A* 4B 3C 1Journal 20Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	EigenShield: Inference-Time, Model-Agnostic Jailbreaking Defense via Causal Subspace Filtering. AAAI Nastaran Darabi, Devashri Naik, Sina Tayebati, Dinithi Jayasuriya, Ranganath Krishnan, Amit Ranjan Trivedi
2026	J	`jnl`	HEAL: Brain-Inspired Hyperdimensional Efficient Active Learning. IEEE Trans. Artif. Intell. Yang Ni, Zhuowen Zou, Wenjun Huang, Hanning Chen, William Youngwoo Chung, Samuel Cho, Ranganath Krishnan, Pietro Mercati, Mohsen Imani
2026	J	`jnl`	TRACER: Trajectory Risk Aggregation for Critical Episodes in Agentic Reasoning. CoRR Sina Tayebati, Divake Kumar, Nastaran Darabi, Davide Ettori, Ranganath Krishnan, Amit Ranjan Trivedi
2025	J	`jnl`	EigenShield: Causal Subspace Filtering via Random Matrix Theory for Adversarially Robust Vision-Language Models. CoRR Nastaran Darabi, Devashri Naik, Sina Tayebati, Dinithi Jayasuriya, Ranganath Krishnan, Amit Ranjan Trivedi
2025	J	`jnl`	EigenTrack: Spectral Activation Feature Tracking for Hallucination and Out-of-Distribution Detection in LLMs and VLMs. CoRR Davide Ettori, Nastaran Darabi, Sina Tayebati, Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo, Amit Ranjan Trivedi
2025	J	`jnl`	Learnable Conformal Prediction with Context-Aware Nonconformity Functions for Robotic Planning and Perception. CoRR Divake Kumar, Sina Tayebati, Francesco Migliarba, Ranganath Krishnan, Amit Ranjan Trivedi
2025	J	`jnl`	Learning Conformal Abstention Policies for Adaptive Risk Management in Large Language and Vision-Language Models. CoRR Sina Tayebati, Divake Kumar, Nastaran Darabi, Dinithi Jayasuriya, Ranganath Krishnan, Amit Ranjan Trivedi
2025	B	`conf`	Optimizing Active Learning in Vision-Language Models via Parameter-Efficient Uncertainty Calibration. IJCNN Athmanarayanan Lakshmi Narayanan, Amrutha Machireddy, Ranganath Krishnan
2025	J	`jnl`	Optimizing Active Learning in Vision-Language Models via Parameter-Efficient Uncertainty Calibration. CoRR Athmanarayanan Lakshmi Narayanan, Amrutha Machireddy, Ranganath Krishnan
2025	B	`conf`	SPARC: Subspace-Aware Prompt Adaptation for Robust Continual Learning in LLMs. IJCNN Dinithi Jayasuriya, Sina Tayebati, Davide Ettori, Ranganath Krishnan, Amit Ranjan Trivedi
2025	J	`jnl`	SPARC: Subspace-Aware Prompt Adaptation for Robust Continual Learning in LLMs. CoRR Dinithi Jayasuriya, Sina Tayebati, Davide Ettori, Ranganath Krishnan, Amit Ranjan Trivedi
2024	J	`jnl`	Enhancing Trust in Large Language Models with Uncertainty-Aware Fine-Tuning. CoRR Ranganath Krishnan, Piyush Khanna, Omesh Tickoo
2024	J	`jnl`	HEAL: Brain-inspired Hyperdimensional Efficient Active Learning. CoRR Yang Ni, Zhuowen Zou, Wenjun Huang, Hanning Chen, William Youngwoo Chung, Samuel Cho, Ranganath Krishnan, Pietro Mercati, Mohsen Imani
2024	J	`jnl`	Parameter-Efficient Active Learning for Foundational models. CoRR Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh Subedar
2024	B	`conf`	Source-Free Continual Adaptive Learning With Limited Labels on Evolving Data Drifts. ICIP Amrutha Machireddy, Ranganath Krishnan, Athmanarayanan Lakshmi Narayanan, Omesh Tickoo
2023	—	`conf`	Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness. IISWC Jun-Liang Lin, Ranganath Krishnan, Keyur Ruganathbhai Ranipa, Mahesh Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Taylan Kandemir
2022	—	`conf`	Continual Active Adaptation to Evolving Distributional Shifts. CVPR Workshops Amrutha Machireddy, Ranganath Krishnan, Nilesh A. Ahuja, Omesh Tickoo
2022	—	`conf`	Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization. ECCV Workshops (5) Neslihan Kose, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch
2022	J	`jnl`	Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization. CoRR Neslihan Kose, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch
2021	J	`jnl`	Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR Ranganath Krishnan, Nilesh A. Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
2021	J	`jnl`	Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR Ranganath Krishnan, Alok Sinha, Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
2021	C	`conf`	Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. AIES Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang
2020	A*	`conf`	Improving model calibration with accuracy versus uncertainty optimization. NeurIPS Ranganath Krishnan, Omesh Tickoo
2020	J	`jnl`	Improving model calibration with accuracy versus uncertainty optimization. CoRR Ranganath Krishnan, Omesh Tickoo
2020	A*	`conf`	Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. AAAI Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
2020	J	`jnl`	Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. CoRR Umang Bhatt, Yunfeng Zhang, Javier Antorán, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Adrian Weller, Alice Xiang
2019	J	`jnl`	Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo
2019	—	`conf`	Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks. ICCV Workshops Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
2019	J	`jnl`	MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks. CoRR Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
2019	—	`conf`	Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference. CVPR Workshops Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
2019	A*	`conf`	Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference. ICCV Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
2018	J	`jnl`	BAR: Bayesian Activity Recognition using variational inference. CoRR Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
2018	J	`jnl`	Uncertainty aware multimodal activity recognition with Bayesian inference. CoRR Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang