Dmitry Kalashnikov

According to our database1, Dmitry Kalashnikov authored at least 21 papers between 2018 and 2023.

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Bibliography

2023
Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
CoRR, 2023



2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.
CoRR, 2022

Hybrid Random Features.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation.
Proceedings of the Conference on Robot Learning, 2022


2021
AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale.
CoRR, 2021

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale.
CoRR, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.
CoRR, 2021

Reward Machines for Vision-Based Robotic Manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Visionary: Vision architecture discovery for robot learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.
Proceedings of the 38th International Conference on Machine Learning, 2021

AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Scaling Up Multi-Task Robotic Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Disentangled Planning and Control in Vision Based Robotics via Reward Machines.
CoRR, 2020

Learning Precise 3D Manipulation from Multiple Uncalibrated Cameras.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.
CoRR, 2018

Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018


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