Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks

1 code implementation • 21 Oct 2022 • Zhile Yang, Shangqi Guo, Ying Fang, Jian K. Liu

One stream of reinforcement learning research is exploring biologically plausible models and algorithms to simulate biological intelligence and fit neuromorphic hardware.

Reinforcement Learning (RL)

Success-Rate Targeted Reinforcement Learning by Disorientation Penalty

no code implementations • 1 Jan 2021 • Haichuan Gao, Zhile Yang, Tian Tan, Feng Chen

Unfortunately, applying traditional Bellman updates to value function learning can be problematic for learning undiscounted return, and thus not suitable for optimizing success rate.

Decision Making Q-Learning +2

Distributed Fusion Estimation for Stochastic Uncertain Systems with Network-Induced Complexity and Multiple Noise

no code implementations • 24 Dec 2020 • Li Liu, Wenju Zhou, Minrui Fei, Zhile Yang, Hongyong Yang, Huiyu Zhou

This paper investigates an issue of distributed fusion estimation under network-induced complexity and stochastic parameter uncertainties.

Structured Context Enhancement Network for Mouse Pose Estimation

1 code implementation • 1 Dec 2020 • Feixiang Zhou, Zheheng Jiang, Zhihua Liu, Fang Chen, Long Chen, Lei Tong, Zhile Yang, Haikuan Wang, Minrui Fei, Ling Li, Huiyu Zhou

However, quantifying mouse behaviours from videos or images remains a challenging problem, where pose estimation plays an important role in describing mouse behaviours.

Animal Pose Estimation

A Novel Deep Neural Network Based Approach for Sparse Code Multiple Access

no code implementations • 4 Jun 2019 • Jinzhi Lin, Shengzhong Feng, Zhile Yang, Yun Zhang, Yong Zhang

Furthermore, by manipulating the mapping vectors, an autoencoder is able to generalize SCMA, thus a dense code multiple access (DCMA) scheme is proposed.