no code implementations • 28 Feb 2025 • Songrun He, Linying Lv, Asaf Manela, Jimmy Wu
Large language models are increasingly used in social sciences, but their training data can introduce lookahead bias and training leakage.
no code implementations • 11 Dec 2024 • Jimmy Wu, William Chong, Robert Holmberg, Aaditya Prasad, Yihuai Gao, Oussama Khatib, Shuran Song, Szymon Rusinkiewicz, Jeannette Bohg
In our experiments, we use this interface to collect data and show that the resulting learned policies can successfully perform a variety of common household mobile manipulation tasks.
no code implementations • 13 May 2024 • Aaditya Prasad, Kevin Lin, Jimmy Wu, Linqi Zhou, Jeannette Bohg
Many robotic systems, such as mobile manipulators or quadrotors, cannot be equipped with high-end GPUs due to space, weight, and power constraints.
1 code implementation • 9 May 2023 • Jimmy Wu, Rika Antonova, Adam Kan, Marion Lepert, Andy Zeng, Shuran Song, Jeannette Bohg, Szymon Rusinkiewicz, Thomas Funkhouser
For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios.
no code implementations • 15 Jun 2022 • Jimmy Wu, Yatong Chen, Yang Liu
We study the problem of classifier derandomization in machine learning: given a stochastic binary classifier $f: X \to [0, 1]$, sample a deterministic classifier $\hat{f}: X \to \{0, 1\}$ that approximates the output of $f$ in aggregate over any data distribution.
1 code implementation • 5 Apr 2022 • Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser
We investigate pneumatic non-prehensile manipulation (i. e., blowing) as a means of efficiently moving scattered objects into a target receptacle.
1 code implementation • 23 Mar 2021 • Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser
The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks.
no code implementations • 7 Sep 2020 • Zhaoyu Su, Pin Siang Tan, Junkang Chow, Jimmy Wu, Yehur Cheong, Yu-Hsing Wang
3D point cloud interpretation is a challenging task due to the randomness and sparsity of the component points.
1 code implementation • 20 Apr 2020 • Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Johnny Lee, Szymon Rusinkiewicz, Thomas Funkhouser
Typical end-to-end formulations for learning robotic navigation involve predicting a small set of steering command actions (e. g., step forward, turn left, turn right, etc.)
2 code implementations • 3 Aug 2018 • Jimmy Wu, Bolei Zhou, Rebecca Russell, Vincent Kee, Syler Wagner, Mitchell Hebert, Antonio Torralba, David M. S. Johnson
In this work, we introduce pose interpreter networks for 6-DoF object pose estimation.
1 code implementation • 31 May 2018 • Jimmy Wu, Bolei Zhou, Diondra Peck, Scott Hsieh, Vandana Dialani, Lester Mackey, Genevieve Patterson
We propose DeepMiner, a framework to discover interpretable representations in deep neural networks and to build explanations for medical predictions.
1 code implementation • 13 Mar 2018 • Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson
This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms.
2 code implementations • 5 Mar 2017 • Jay M. Wong, Vincent Kee, Tiffany Le, Syler Wagner, Gian-Luca Mariottini, Abraham Schneider, Lei Hamilton, Rahul Chipalkatty, Mitchell Hebert, David M. S. Johnson, Jimmy Wu, Bolei Zhou, Antonio Torralba
Recent robotic manipulation competitions have highlighted that sophisticated robots still struggle to achieve fast and reliable perception of task-relevant objects in complex, realistic scenarios.