Danny Driess

About Danny Driess

Danny Driess, With an exceptional h-index of 19 and a recent h-index of 19 (since 2020), a distinguished researcher at Universität Stuttgart, specializes in the field of Machine Learning, Robotics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Towards generalist biomedical ai

Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Spatialvlm: Endowing vision-language models with spatial reasoning capabilities

Learning multi-object dynamics with compositional neural radiance fields

Foundation models in robotics: Applications, challenges, and the future

Rt-2: Vision-language-action models transfer web knowledge to robotic control

Open x-embodiment: Robotic learning datasets and RT-x models

Danny Driess Information

University

Position

___

Citations(all)

1534

Citations(since 2020)

1522

Cited By

136

hIndex(all)

19

hIndex(since 2020)

19

i10Index(all)

27

i10Index(since 2020)

27

Email

University Profile Page

Google Scholar

Danny Driess Skills & Research Interests

Machine Learning

Robotics

Top articles of Danny Driess

Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents

arXiv preprint arXiv:2303.00855

2023/3/1

Spatialvlm: Endowing vision-language models with spatial reasoning capabilities

arXiv preprint arXiv:2401.12168

2024/1/22

Learning multi-object dynamics with compositional neural radiance fields

2023/3/6

Foundation models in robotics: Applications, challenges, and the future

arXiv preprint arXiv:2312.07843

2023/12/13

Open x-embodiment: Robotic learning datasets and RT-x models

arXiv preprint arXiv:2310.08864

2023/10/13

Large language models as general pattern machines

7th Annual Conference on Robot Learning

2023/7/10

Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning

2023/5/29

Palm-e: An embodied multimodal language model

The International Conference on Machine Learning

2023/3/6

Reinforcement learning with neural radiance fields

Advances in Neural Information Processing Systems

2022/12/6

FC3: Feasibility-Based Control Chain Coordination

2022/10/23

Danny Driess
Danny Driess

H-Index: 8

Marc Toussaint
Marc Toussaint

H-Index: 31

Sequence-of-constraints mpc: Reactive timing-optimal control of sequential manipulation

2022/10/23

Long-horizon multi-robot rearrangement planning for construction assembly

IEEE Transactions on Robotics

2022

Deep visual constraints: Neural implicit models for manipulation planning from visual input

IEEE Robotics and Automation Letters, 2022

2021/12/9

Structured deep generative models for sampling on constraint manifolds in sequential manipulation

2022/1/11

Learning models as functionals of signed-distance fields for manipulation planning

2022/1/11

Learning to execute: Efficient learning of universal plan-conditioned policies in robotics

Advances in Neural Information Processing Systems

2021/12/6

Learning to solve sequential physical reasoning problems from a scene image

The International Journal of Robotics Research

2021/12

See List of Professors in Danny Driess University(Universität Stuttgart)

Co-Authors

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