1 code implementation • 26 Oct 2023 • Yifei Peng, Yu Jin, Zhexu Luo, Yao-Xiang Ding, Wang-Zhou Dai, Zhong Ren, Kun Zhou
There are two levels of symbol grounding problems among the core challenges: the first is symbol assignment, i. e. mapping latent factors of neural visual generators to semantic-meaningful symbolic factors from the reasoning systems by learning from limited labeled data.
no code implementations • 24 Aug 2023 • Lun Ai, Shi-Shun Liang, Wang-Zhou Dai, Liam Hallett, Stephen H. Muggleton, Geoff S. Baldwin
An important application of Synthetic Biology is the engineering of the host cell system to yield useful products.
1 code implementation • 21 Aug 2023 • Lue Tao, Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang
Neuro-symbolic hybrid systems are promising for integrating machine learning and symbolic reasoning, where perception models are facilitated with information inferred from a symbolic knowledge base through logical reasoning.
1 code implementation • NeurIPS 2021 • Yu-Xuan Huang, Wang-Zhou Dai, Le-Wen Cai, Stephen Muggleton, Yuan Jiang
To utilize the raw inputs and symbolic knowledge simultaneously, some recent neuro-symbolic learning methods use abduction, i. e., abductive reasoning, to integrate sub-symbolic perception and logical inference.
no code implementations • 17 May 2021 • Wang-Zhou Dai, Liam Hallett, Stephen H. Muggleton, Geoff S. Baldwin
The application of Artificial Intelligence (AI) to synthetic biology will provide the foundation for the creation of a high throughput automated platform for genetic design, in which a learning machine is used to iteratively optimise the system through a design-build-test-learn (DBTL) cycle.
1 code implementation • 7 Oct 2020 • Wang-Zhou Dai, Stephen H. Muggleton
In this paper, we present Abductive Meta-Interpretive Learning ($Meta_{Abd}$) that unites abduction and induction to learn neural networks and induce logic theories jointly from raw data.
1 code implementation • NeurIPS 2019 • Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu, Zhi-Hua Zhou
In the area of artificial intelligence (AI), the two abilities are usually realised by machine learning and logic programming, respectively.
1 code implementation • 4 Feb 2018 • Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu, Zhi-Hua Zhou
Perception and reasoning are basic human abilities that are seamlessly connected as part of human intelligence.
no code implementations • 25 Feb 2014 • Wang-Zhou Dai, Zhi-Hua Zhou
Structure learning of these systems is an intersection area of Inductive Logic Programming (ILP) and statistical learning (SL).