18 citations · 96 across the 23 of their papers we have counts for
10 papers · 1 filter
Neuro-Symbolic Hierarchical Rule Induction
Claire Glanois, Xuening Feng, Zhaohui Jiang +4
We propose an efficient interpretable neuro-symbolic model to solve Inductive Logic Programming (ILP) problems. In this model, which is built from a set of meta-rules organised in…
New physics in semileptonic transitions: rare hyperon vs. kaon decays
Li-Sheng Geng, Jorge Martin Camalich, Rui-Xiang Shi
We investigate the potential of rare hyperon decays to probe the short distance structure in the and transitions. Hyperon decays into neutrinos…
SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Hangyu Mao, Chao Wang, Xiaotian Hao +6
The MineRL competition is designed for the development of reinforcement learning and imitation learning algorithms that can efficiently leverage human demonstrations to drastically…
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction
Amur Ghose, Vincent Zhang, Yingxue Zhang +3
Presently with technology node scaling, an accurate prediction model at early design stages can significantly reduce the design cycle. Especially during logic synthesis, predicting…
Learning State Representations via Retracing in Reinforcement Learning
Changmin Yu, Dong Li, Jianye Hao +2
We propose learning via retracing, a novel self-supervised approach for learning the state representation (and the associated dynamics model) for reinforcement learning tasks. In a…
Empirical Policy Optimization for -Player Markov Games
Yuanheng Zhu, Dongbin Zhao, Mengchen Zhao +1
In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment. In multi-player Markov games (MGs), however, the interaction…