Viktor Makoviychuk

Orcid: 0009-0002-1053-8229

According to our database1, Viktor Makoviychuk authored at least 18 papers between 2018 and 2024.

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Bibliography

2024
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.
CoRR, 2024

2023
Learning Physically Simulated Tennis Skills from Broadcast Videos.
ACM Trans. Graph., August, 2023

DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Training.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality.
CoRR, 2022

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Accelerated Policy Learning with Parallel Differentiable Simulation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions.
CoRR, 2021

Isaac Gym: High Performance GPU Based Physics Simulation For Robot Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
CoRR, 2020

In-Hand Object Pose Tracking via Contact Feedback and GPU-Accelerated Robotic Simulation.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019
Non-smooth Newton Methods for Deformable Multi-body Dynamics.
ACM Trans. Graph., 2019

Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience.
Proceedings of the International Conference on Robotics and Automation, 2019

2018
Physics-based motion capture imitation with deep reinforcement learning.
Proceedings of the 11th Annual International Conference on Motion, Interaction, and Games, 2018

GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018


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