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Found 9 papers, 6 papers with code
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
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.
Human Comprehensible Active Learning of Genome-Scale Metabolic Networks
An important application of Synthetic Biology is the engineering of the host cell system to yield useful products.
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
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.
Fast Abductive Learning by Similarity-based Consistency Optimization
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.
Automated Biodesign Engineering by Abductive Meta-Interpretive Learning
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.
Abductive Knowledge Induction From Raw Data
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.
Bridging Machine Learning and Logical Reasoning by Abductive Learning
In the area of artificial intelligence (AI), the two abilities are usually realised by machine learning and logic programming, respectively.
Tunneling Neural Perception and Logic Reasoning through Abductive Learning
Perception and reasoning are basic human abilities that are seamlessly connected as part of human intelligence.
Inductive Logic Boosting
Structure learning of these systems is an intersection area of Inductive Logic Programming (ILP) and statistical learning (SL).
