no code implementations • 25 Jul 2023 • Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, Allan Zhao, Amy Zhu, Wil J Norton, Edward Gu, Joshua Jacob, Yifei Li, Adriana Schulz, Wojciech Matusik
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design.
no code implementations • 29 Sep 2021 • Michal Piovarci, Michael Foshey, Timothy Erps, Jie Xu, Vahid Babaei, Piotr Didyk, Wojciech Matusik, Szymon Rusinkiewicz, Bernd Bickel
We further show that in combination with reinforcement learning, our model can be used to discover control policies that outperform state-of-the-art controllers.
no code implementations • 29 Sep 2021 • Yunsheng Tian, Mina Konakovic Lukovic, Michael Foshey, Timothy Erps, Beichen Li, Wojciech Matusik
We present AutoOED, an Automated Optimal Experimental Design platform powered by machine learning to accelerate discovering solutions with optimal objective trade-offs.
no code implementations • 9 Sep 2021 • Qiang Zhang, Yunzhu Li, Yiyue Luo, Wan Shou, Michael Foshey, Junchi Yan, Joshua B. Tenenbaum, Wojciech Matusik, Antonio Torralba
This work takes a step on dynamics modeling in hand-object interactions from dense tactile sensing, which opens the door for future applications in activity learning, human-computer interactions, and imitation learning for robotics.
1 code implementation • 15 Jul 2021 • Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal
Existing methods for co-optimization are limited and fail to explore a rich space of designs.
no code implementations • CVPR 2021 • Yiyue Luo, Yunzhu Li, Michael Foshey, Wan Shou, Pratyusha Sharma, Tomas Palacios, Antonio Torralba, Wojciech Matusik
In this work, leveraging such tactile interactions, we propose a 3D human pose estimation approach using the pressure maps recorded by a tactile carpet as input.
no code implementations • 5 May 2021 • Minghao Guo, Wan Shou, Liane Makatura, Timothy Erps, Michael Foshey, Wojciech Matusik
Here, we present a parametric, context-sensitive grammar designed specifically for the representation and generation of polymers.
1 code implementation • 13 Apr 2021 • Yunsheng Tian, Mina Konaković Luković, Timothy Erps, Michael Foshey, Wojciech Matusik
We present AutoOED, an Optimal Experiment Design platform powered with automated machine learning to accelerate the discovery of optimal solutions.