Search Results for author: Ruihan Yang

Found 19 papers, 10 papers with code

Lossy Image Compression with Conditional Diffusion Models

no code implementations14 Sep 2022 Ruihan Yang, Stephan Mandt

This paper outlines an end-to-end optimized lossy image compression framework using diffusion generative models.

Denoising Image Compression +2

Diffusion Probabilistic Modeling for Video Generation

1 code implementation16 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.

Denoising Image Generation +2

SC2: Supervised Compression for Split Computing

1 code implementation16 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.

Data Compression Edge-computing +2

Vision-Guided Quadrupedal Locomotion in the Wild with Multi-Modal Delay Randomization

1 code implementation29 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.

Reinforcement Learning (RL)

Supervised Compression for Resource-Constrained Edge Computing Systems

2 code implementations21 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.

Data Compression Edge-computing +2

DexMV: Imitation Learning for Dexterous Manipulation from Human Videos

no code implementations12 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.

Imitation Learning motion retargeting +1

Insights from Generative Modeling for Neural Video Compression

no code implementations28 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.

Video Compression

Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers

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.

Reinforcement Learning (RL)

SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS

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.

Dimensionality Reduction Video Compression

Generative Video Compression as Hierarchical Variational Inference

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.

Density Estimation Variational Inference +1

Hierarchical Autoregressive Modeling for Neural Video Compression

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.

Density Estimation Video Compression

PIANOTREE VAE: Structured Representation Learning for Polyphonic Music

2 code implementations17 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).

Music Generation Representation Learning

Multi-Task Reinforcement Learning with Soft Modularization

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.

Meta-Learning Multi-Task Learning +2

Suphx: Mastering Mahjong with Deep Reinforcement Learning

no code implementations30 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.

reinforcement-learning Reinforcement Learning (RL)

Deep Music Analogy Via Latent Representation Disentanglement

3 code implementations9 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.

Disentanglement

Inspecting and Interacting with Meaningful Music Representations using VAE

no code implementations18 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.

Disentanglement Image Generation +1

MatchBench: An Evaluation of Feature Matchers

no code implementations7 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.

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