15 citations · 20 across the 18 of their papers we have counts for
5 papers · 1 filter
Neural Combinatorial Logic Circuit Synthesis from Input-Output Examples
Peter Belcak, Roger Wattenhofer
We propose a novel, fully explainable neural approach to synthesis of combinatorial logic circuits from input-output examples. The carrying advantage of our method is that it readi…
A Neural Model for Regular Grammar Induction
Peter Belcák, David Hofer, Roger Wattenhofer
Grammatical inference is a classical problem in computational learning theory and a topic of wider influence in natural language processing. We treat grammars as a model of computa…
Periodic Extrapolative Generalisation in Neural Networks
Peter Belcák, Roger Wattenhofer
The learning of the simplest possible computational pattern -- periodicity -- is an open problem in the research of strong generalisation in neural networks. We formalise the probl…
FACT: Learning Governing Abstractions Behind Integer Sequences
Peter Belcák, Ard Kastrati, Flavio Schenker +1
Integer sequences are of central importance to the modeling of concepts admitting complete finitary descriptions. We introduce a novel view on the learning of such concepts and lay…
Deterministic Graph-Walking Program Mining
Peter Belcak, Roger Wattenhofer
Owing to their versatility, graph structures admit representations of intricate relationships between the separate entities comprising the data. We formalise the notion of connecti…