Vikranth Reddy Dwaracherla

According to our database, Vikranth Reddy Dwaracherla authored at least 15 papers between 2016 and 2024.

Collaborative distances:

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

2024

Efficient Exploration for LLMs.

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping.

Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy

Trans. Mach. Learn. Res., 2023

Reinforcement Learning, Bit by Bit.

Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen

Found. Trends Mach. Learn., 2023

Approximate Thompson Sampling via Epistemic Neural Networks.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Epistemic Neural Networks.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Robustness of Epinets against Distributional Shifts.

Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy

CoRR, 2022

Evaluating high-order predictive distributions in deep learning.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Uncertainty in Artificial Intelligence, 2022

The Neural Testbed: Evaluating Joint Predictions.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy

CoRR, 2021

2020

Langevin DQN.

Vikranth Dwaracherla, Benjamin Van Roy

CoRR, 2020

Hypermodels for Exploration.

Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy

Proceedings of the 8th International Conference on Learning Representations, 2020

2018

Motion-Based Object Segmentation Based on Dense RGB-D Scene Flow.

Lin Shao, Parth Shah, Vikranth Dwaracherla, Jeannette Bohg

IEEE Robotics Autom. Lett., 2018

2017

Gradient Estimation with Simultaneous Perturbation and Compressive Sensing.

Vivek S. Borkar, Vikranth Reddy Dwaracherla, Neeraja Sahasrabudhe

J. Mach. Learn. Res., 2017

2016

Probabilistic Approach for Visual Homing of a Mobile Robot in the Presence of Dynamic Obstacles.

Anupa Sabnis, Arunkumar G. K., Vikranth Reddy Dwaracherla, Leena Vachhani

IEEE Trans. Ind. Electron., 2016

Discrete time position feedback based steering control for autonomous homing of a mobile robot.

Vikranth Reddy Dwaracherla, Shantanu Thakar, G. K. Arun Kumar, Leena Vachhani

Proceedings of the 12th IEEE International Conference on Control and Automation, 2016