Ranganath Krishnan

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Variational Inference

Top Venues

ECCV Workshops (5)

Publications

Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh Subedar
Parameter-Efficient Active Learning for Foundational models. CoRR (2024)
Yang Ni, Zhuowen Zou, Wenjun Huang, Hanning Chen, William Youngwoo Chung, Samuel Cho, Ranganath Krishnan, Pietro Mercati, Mohsen Imani
HEAL: Brain-inspired Hyperdimensional Efficient Active Learning. CoRR (2024)
Jun-Liang Lin, Ranganath Krishnan, Keyur Ruganathbhai Ranipa, Mahesh Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Taylan Kandemir
Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness. IISWC (2023)
Neslihan Kose, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization. CoRR (2022)
Neslihan Kose, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization. ECCV Workshops (5) (2022)
Amrutha Machireddy, Ranganath Krishnan, Nilesh A. Ahuja, Omesh Tickoo
Continual Active Adaptation to Evolving Distributional Shifts. CVPR Workshops (2022)
Ranganath Krishnan, Alok Sinha, Nilesh Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR (2021)
Ranganath Krishnan, Nilesh Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR (2021)
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
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. AIES (2021)
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
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. CoRR (2020)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. AAAI (2020)
Ranganath Krishnan, Omesh Tickoo
Improving model calibration with accuracy versus uncertainty optimization. CoRR (2020)
Ranganath Krishnan, Omesh Tickoo
Improving model calibration with accuracy versus uncertainty optimization. NeurIPS (2020)
Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo
Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR (2019)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference. CVPR Workshops (2019)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference. ICCV (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks. CoRR (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks. ICCV Workshops (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
BAR: Bayesian Activity Recognition using variational inference. CoRR (2018)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty aware multimodal activity recognition with Bayesian inference. CoRR (2018)