Vikranth Dwaracherla

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Bayesian Logistic Regression

Top Venues

IEEE Robotics Autom. Lett.

Publications

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy
Efficient Exploration for LLMs. CoRR (2024)
Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. Trans. Mach. Learn. Res. 2023 (2023)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
Approximate Thompson Sampling via Epistemic Neural Networks. UAI (2023)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
Approximate Thompson Sampling via Epistemic Neural Networks. CoRR (2023)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
Epistemic Neural Networks. NeurIPS (2023)
Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
Reinforcement Learning, Bit by Bit. Found. Trends Mach. Learn. 16 (6) (2023)
Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy
Robustness of Epinets against Distributional Shifts. CoRR (2022)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
Evaluating high-order predictive distributions in deep learning. UAI (2022)
Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. CoRR (2022)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
Evaluating High-Order Predictive Distributions in Deep Learning. CoRR (2022)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy
The Neural Testbed: Evaluating Joint Predictions. NeurIPS (2022)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? CoRR (2021)
Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
Reinforcement Learning, Bit by Bit. CoRR (2021)
Vikranth Dwaracherla, Benjamin Van Roy
Langevin DQN. CoRR (2020)
Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
Hypermodels for Exploration. ICLR (2020)
Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
Hypermodels for Exploration. CoRR (2020)
Lin Shao, Parth Shah, Vikranth Dwaracherla, Jeannette Bohg
Motion-based Object Segmentation based on Dense RGB-D Scene Flow. CoRR (2018)
Lin Shao, Parth Shah, Vikranth Dwaracherla, Jeannette Bohg
Motion-Based Object Segmentation Based on Dense RGB-D Scene Flow. IEEE Robotics Autom. Lett. 3 (4) (2018)