no code implementations • 14 Sep 2022 • Ruihan Yang, Stephan Mandt
This paper outlines an end-to-end optimized lossy image compression framework using diffusion generative models.
1 code implementation • 16 Mar 2022 • Ruihan Yang, Prakhar Srivastava, Stephan Mandt
Denoising diffusion probabilistic models are a promising new class of generative models that mark a milestone in high-quality image generation.
1 code implementation • 16 Mar 2022 • Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
Split computing distributes the execution of a neural network (e. g., for a classification task) between a mobile device and a more powerful edge server.
1 code implementation • 29 Sep 2021 • Chieko Sarah Imai, Minghao Zhang, Yuchen Zhang, Marcin Kierebinski, Ruihan Yang, Yuzhe Qin, Xiaolong Wang
While Reinforcement Learning (RL) provides a promising paradigm for agile locomotion skills with vision inputs in simulation, it is still very challenging to deploy the RL policy in the real world.
2 code implementations • 21 Aug 2021 • Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
There has been much interest in deploying deep learning algorithms on low-powered devices, including smartphones, drones, and medical sensors.
no code implementations • 12 Aug 2021 • Yuzhe Qin, Yueh-Hua Wu, Shaowei Liu, Hanwen Jiang, Ruihan Yang, Yang Fu, Xiaolong Wang
While significant progress has been made on understanding hand-object interactions in computer vision, it is still very challenging for robots to perform complex dexterous manipulation.
no code implementations • 28 Jul 2021 • Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
While recent machine learning research has revealed connections between deep generative models such as VAEs and rate-distortion losses used in learned compression, most of this work has focused on images.
1 code implementation • ICLR 2022 • Ruihan Yang, Minghao Zhang, Nicklas Hansen, Huazhe Xu, Xiaolong Wang
Our key insight is that proprioceptive states only offer contact measurements for immediate reaction, whereas an agent equipped with visual sensory observations can learn to proactively maneuver environments with obstacles and uneven terrain by anticipating changes in the environment many steps ahead.
no code implementations • ICLR Workshop Neural_Compression 2021 • Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
There has been a recent surge of interest in neural video compression models that combines data-driven dimensionality reduction with learned entropy coding.
no code implementations • pproximateinference AABI Symposium 2021 • Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
Recent work by Marino et al. (2020) showed improved performance in sequential density estimation by combining masked autoregressive flows with hierarchical latent variable models.
1 code implementation • ICLR 2021 • Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
Recent work by Marino et al. (2020) showed improved performance in sequential density estimation by combining masked autoregressive flows with hierarchical latent variable models.
2 code implementations • 17 Aug 2020 • Ziyu Wang, Yiyi Zhang, Yixiao Zhang, Junyan Jiang, Ruihan Yang, Junbo Zhao, Gus Xia
The dominant approach for music representation learning involves the deep unsupervised model family variational autoencoder (VAE).
1 code implementation • NeurIPS 2020 • Ruihan Yang, Huazhe Xu, Yi Wu, Xiaolong Wang
While training multiple tasks jointly allow the policies to share parameters across different tasks, the optimization problem becomes non-trivial: It remains unclear what parameters in the network should be reused across tasks, and how the gradients from different tasks may interfere with each other.
Ranked #1 on
Meta-Learning
on MT50
no code implementations • 30 Mar 2020 • Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon
Artificial Intelligence (AI) has achieved great success in many domains, and game AI is widely regarded as its beachhead since the dawn of AI.
3 code implementations • 9 Jun 2019 • Ruihan Yang, Dingsu Wang, Ziyu Wang, Tianyao Chen, Junyan Jiang, Gus Xia
Analogy-making is a key method for computer algorithms to generate both natural and creative music pieces.
no code implementations • 28 May 2019 • Ruihan Yang, Qiwei Ye, Tie-Yan Liu
Based on that, We proposed an end-to-end algorithm to learn exploration policy by meta-learning.
no code implementations • 18 Apr 2019 • Ruihan Yang, Tianyao Chen, Yiyi Zhang, Gus Xia
Variational Autoencoders(VAEs) have already achieved great results on image generation and recently made promising progress on music generation.
1 code implementation • 7 Feb 2019 • Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty, Jennifer Hicks, Sean F. Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaśkowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy Watson, Marcel Salathé, Sergey Levine, Scott Delp
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector.
no code implementations • 7 Aug 2018 • Jia-Wang Bian, Ruihan Yang, Yun Liu, Le Zhang, Ming-Ming Cheng, Ian Reid, WenHai Wu
This leads to a critical absence in this field that there is no standard datasets and evaluation metrics to evaluate different feature matchers fairly.