Ranganath Krishnan

According to our database, Ranganath Krishnan authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Parameter-Efficient Active Learning for Foundational models.

Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh Subedar

CoRR, 2024

HEAL: Brain-inspired Hyperdimensional Efficient Active Learning.

Yang Ni, Zhuowen Zou, Wenjun Huang, Hanning Chen, William Youngwoo Chung, Samuel Cho, Ranganath Krishnan, Pietro Mercati, Mohsen Imani

CoRR, 2024

2023

Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness.

Jun-Liang Lin, Ranganath Krishnan, Keyur Ruganathbhai Ranipa, Mahesh Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Taylan Kandemir

Proceedings of the IEEE International Symposium on Workload Characterization, 2023

2022

Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization.

Neslihan Kose, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Continual Active Adaptation to Evolving Distributional Shifts.

Amrutha Machireddy, Ranganath Krishnan, Nilesh A. Ahuja, Omesh Tickoo

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Improving Robustness and Efficiency in Active Learning with Contrastive Loss.

Ranganath Krishnan, Nilesh A. Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer

CoRR, 2021

Mitigating Sampling Bias and Improving Robustness in Active Learning.

Ranganath Krishnan, Alok Sinha, Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer

CoRR, 2021

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

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

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

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

CoRR, 2020

Improving model calibration with accuracy versus uncertainty optimization.

Ranganath Krishnan, Omesh Tickoo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes.

Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep Probabilistic Models to Detect Data Poisoning Attacks.

Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo

CoRR, 2019

MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks.

Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo

CoRR, 2019

Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks.

Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference.

Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Uncertainty aware multimodal activity recognition with Bayesian inference.

Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang

CoRR, 2018

BAR: Bayesian Activity Recognition using variational inference.

Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo

CoRR, 2018