no code implementations • 10 Mar 2023 • Kei Ota, Devesh K. Jha, Hsiao-Yu Tung, Joshua B. Tenenbaum
We evaluate our method on several part-mating tasks with novel objects using a robot equipped with a vision-based tactile sensor.
1 code implementation • 4 Mar 2023 • Zhou Xian, Bo Zhu, Zhenjia Xu, Hsiao-Yu Tung, Antonio Torralba, Katerina Fragkiadaki, Chuang Gan
We identify several challenges for fluid manipulation learning by evaluating a set of reinforcement learning and trajectory optimization methods on our platform.
no code implementations • 22 Oct 2022 • Kei Ota, Hsiao-Yu Tung, Kevin A. Smith, Anoop Cherian, Tim K. Marks, Alan Sullivan, Asako Kanezaki, Joshua B. Tenenbaum
The world is filled with articulated objects that are difficult to determine how to use from vision alone, e. g., a door might open inwards or outwards.
no code implementations • 17 Mar 2021 • Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Emmanouil Antonios Platanios, Katerina Fragkiadaki
We propose HyperDynamics, a dynamics meta-learning framework that conditions on an agent's interactions with the environment and optionally its visual observations, and generates the parameters of neural dynamics models based on inferred properties of the dynamical system.
no code implementations • ICLR 2021 • Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Emmanouil Antonios Platanios, Katerina Fragkiadaki
We propose HyperDynamics, a framework that conditions on an agent’s interactions with the environment and optionally its visual observations, and generates the parameters of neural dynamics models based on inferred properties of the dynamical system.
1 code implementation • ICLR 2021 • Mihir Prabhudesai, Shamit Lal, Darshan Patil, Hsiao-Yu Tung, Adam W Harley, Katerina Fragkiadaki
We present neural architectures that disentangle RGB-D images into objects' shapes and styles and a map of the background scene, and explore their applications for few-shot 3D object detection and few-shot concept classification.
1 code implementation • 14 Nov 2016 • Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, Arthur Gretton
In this context, the MMD may be used in two roles: first, as a discriminator, either directly on the samples, or on features of the samples.
no code implementations • NeurIPS 2015 • Yining Wang, Hsiao-Yu Tung, Alexander Smola, Animashree Anandkumar
Such tensor contractions are encountered in decomposition methods such as tensor power iterations and alternating least squares.
no code implementations • NeurIPS 2014 • Hsiao-Yu Tung, Alexander J. Smola
The Indian Buffet Process is a versatile statistical tool for modeling distributions over binary matrices.