Vikranth Dwaracherla

21 papers A* 4A 2Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Exploration at Scale. CoRR Seyed Mohammad Asghari, Chris Chute, Vikranth Dwaracherla, Xiuyuan Lu, Mehdi Jafarnia, Victor Minden, Zheng Wen, Benjamin Van Roy
2024	A*	`conf`	Efficient Exploration for LLMs. ICML Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy
2024	J	`jnl`	Efficient Exploration for LLMs. CoRR Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy
2024	—	`conf`	Langevin DQN. CDC Vikranth Dwaracherla, Benjamin Van Roy
2023	A	`conf`	Approximate Thompson Sampling via Epistemic Neural Networks. UAI Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Approximate Thompson Sampling via Epistemic Neural Networks. CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. Trans. Mach. Learn. Res. Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
2023	A*	`conf`	Epistemic Neural Networks. NeurIPS Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Reinforcement Learning, Bit by Bit. Found. Trends Mach. Learn. Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
2022	J	`jnl`	Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. CoRR Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
2022	J	`jnl`	Evaluating High-Order Predictive Distributions in Deep Learning. CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
2022	A	`conf`	Evaluating high-order predictive distributions in deep learning. UAI Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
2022	J	`jnl`	Robustness of Epinets against Distributional Shifts. CoRR Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy
2022	A*	`conf`	The Neural Testbed: Evaluating Joint Predictions. NeurIPS Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy
2021	J	`jnl`	Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy
2021	J	`jnl`	Reinforcement Learning, Bit by Bit. CoRR Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
2020	A*	`conf`	Hypermodels for Exploration. ICLR Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
2020	J	`jnl`	Hypermodels for Exploration. CoRR Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
2020	J	`jnl`	Langevin DQN. CoRR Vikranth Dwaracherla, Benjamin Van Roy
2018	J	`jnl`	Motion-Based Object Segmentation Based on Dense RGB-D Scene Flow. IEEE Robotics Autom. Lett. Lin Shao, Parth Shah, Vikranth Dwaracherla, Jeannette Bohg
2018	J	`jnl`	Motion-based Object Segmentation based on Dense RGB-D Scene Flow. CoRR Lin Shao, Parth Shah, Vikranth Dwaracherla, Jeannette Bohg