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Mel Vecerík
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Conference and Workshop Papers
- 2024
- [c10]Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held:
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. ICLR 2024 - [c9]Mel Vecerík, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, Jon Scholz:
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation. ICRA 2024: 5397-5403 - 2023
- [c8]Carl Doersch, Yi Yang, Mel Vecerík, Dilara Gokay, Ankush Gupta, Yusuf Aytar, João Carreira, Andrew Zisserman:
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement. ICCV 2023: 10027-10038 - 2022
- [c7]Mel Vecerík, Jackie Kay, Raia Hadsell, Lourdes Agapito
, Jon Scholz:
Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings. ICRA 2022: 1251-1257 - 2021
- [c6]Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerík, Ning Ye, Stefan Schaal, Jonathan Scholz:
Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study. Robotics: Science and Systems 2021 - 2020
- [c5]Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz:
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRL 2020: 449-460 - [c4]Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang:
Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems 2020 - 2019
- [c3]Yannick Schroecker, Mel Vecerík, Jonathan Scholz:
Generative predecessor models for sample-efficient imitation learning. ICLR (Poster) 2019 - [c2]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. ICRA 2019: 754-760 - [c1]Kevin Sebastian Luck
, Mel Vecerík, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz:
Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. IROS 2019: 3704-3711
Informal and Other Publications
- 2024
- [i11]Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held:
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. CoRR abs/2404.13478 (2024) - 2023
- [i10]Carl Doersch, Yi Yang, Mel Vecerík, Dilara Gokay, Ankush Gupta, Yusuf Aytar, João Carreira, Andrew Zisserman:
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement. CoRR abs/2306.08637 (2023) - [i9]Mel Vecerík, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, Jon Scholz:
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation. CoRR abs/2308.15975 (2023) - 2021
- [i8]Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerík, Ning Ye, Stefan Schaal, Jonathan Scholz:
Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study. CoRR abs/2103.11512 (2021) - [i7]Mel Vecerík, Jackie Kay, Raia Hadsell, Lourdes Agapito, Jon Scholz:
Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings. CoRR abs/2112.04910 (2021) - 2020
- [i6]Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Christopher Schuster, Raia Hadsell, Lourdes Agapito, Jonathan Scholz:
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRR abs/2009.14711 (2020) - 2019
- [i5]Yannick Schroecker, Mel Vecerík, Jonathan Scholz:
Generative predecessor models for sample-efficient imitation learning. CoRR abs/1904.01139 (2019) - [i4]Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang:
A Framework for Data-Driven Robotics. CoRR abs/1909.12200 (2019) - [i3]Kevin Sebastian Luck, Mel Vecerík, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz:
Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. CoRR abs/1911.06833 (2019) - 2018
- [i2]Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, Gabriel Barth-Maron, Hado van Hasselt, John Quan, Mel Vecerík, Matteo Hessel, Rémi Munos, Olivier Pietquin:
Observe and Look Further: Achieving Consistent Performance on Atari. CoRR abs/1805.11593 (2018) - [i1]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. CoRR abs/1810.01531 (2018)
Coauthor Index
aka: Jon Scholz
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