266 citations · 311 across the 11 of their papers we have counts for
11 papers
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?
Beren Millidge, Tommaso Salvatori, Yuhang Song +2
The backpropagation of error algorithm used to train deep neural networks has been fundamental to the successes of deep learning. However, it requires sequential backward updates a…
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks
Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz +2
Predictive coding networks (PCNs) are an influential model for information processing in the brain. They have appealing theoretical interpretations and offer a single mechanism tha…
Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
Jianyi Wang, Xin Deng, Mai Xu +2
The past few years have witnessed fast development in video quality enhancement via deep learning. Existing methods mainly focus on enhancing the objective quality of compressed vi…
Zeroth-Order Supervised Policy Improvement
Hao Sun, Ziping Xu, Yuhang Song +4
Policy gradient (PG) algorithms have been widely used in reinforcement learning (RL). However, PG algorithms rely on exploiting the value function being learned with the first-orde…
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
Yuhang Song, Andrzej Wojcicki, Thomas Lukasiewicz +6
Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent lea…
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +4
Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic reward…
Diversity-Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +2
Hierarchical reinforcement learning (HRL) has recently shown promising advances on speeding up learning, improving the exploration, and discovering intertask transferable skills. M…
Watching Videos with Certain and Constant Quality: PID-based Quality Control Method
Yuhang Song, Mai Xu, Shengxi Li
In video coding, compressed videos with certain and constant quality can ensure quality of experience (QoE). To this end, we propose in this paper a novel PID-based quality control…
Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach
Yuhang Song, Mai Xu, Jianyi Wang +3
Panoramic video provides immersive and interactive experience by enabling humans to control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in modelin…
Generalization Tower Network: A Novel Deep Neural Network Architecture for Multi-Task Learning
Yuhang Song, Main Xu, Songyang Zhang +1
Deep learning (DL) advances state-of-the-art reinforcement learning (RL), by incorporating deep neural networks in learning representations from the input to RL. However, the conve…
Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting
Christopher Grimm, Yuhang Song, Michael L. Littman
Generative adversarial networks (GANs) are an exciting alternative to algorithms for solving density estimation problems---using data to assess how likely samples are to be drawn f…