Evidence of format independent SNARC effects supports the existence of a common system for symbolic and non-symbolic number processing. Traditionally, it has been considered that both numerical formats share the same neural representation (approximate number system, or ANS) and that non-symbolic numeral...
An atom α is defined as a predicate symbol Pi that acts as a function , which maps the set of variables {x1,x2,⋯,xn} to true or false:(2)α≡Pi(x1,x2,⋯,xn). Although there can be multiple variables in a predicate, we usually only consider the simple unary and binary ...
That something else could be a physical object, an idea, an event, you name it. For our purposes, the sign or symbol is a visual pattern, say a character or string of characters, in which meaning is embedded, and that sign or symbol is pointing at something else. It could be the va...
vectors and the like. The deep learning industry has plenty of folks working on it. It's a multi-billion-dollar industry. We are not competing with that behemoth. The goal of this project is to move forward on sparse-graph knowledge representation. (Note however: some parts of sparse graph...
Such a construction is based on a representation of the unperturbed Hamiltonian and polynomial perturbation operator via generators of the algebra. It was done without an assumption on the separation of independent variables of the perturbation operator and without using fractional powers of the ...
Several models of symbolic number processing consider it as an important component1,4,35. The analogue magnitude representation underlying processing of symbolic numbers is the main focus of this study. The numerical distance effect (NDE) is one of the fundamental characteristics of analogue magnitude...
2.2.1. Feature representation Given a token sequence Xi={xi1,⋯,xiL}, we use an instance encoder to obtain contextual representation Xi. Note that the instance encoder is pluggable, for example, it can be a pre-trained BERT [25], where the token embedding of [CLS] is treated as the...
functions that can be constructed from combinations of addition, subtraction, multiplication, division, and power operators; constant values and distances between atoms; and an operator that performs a sum over functions of distances between a given atom and all neighbors within a given cutoff radius...
The function eval computes the bit pattern representation of the boolean function corresponding to a given CTL formula. For the atomic formulae (a to e, T and F), the result is respectively Abits to Ebits, True and False. For the
The novel aspect of our FFNSL framework is the Data-to-Knowledge (D2K) generator that bridges the neural and symbolic learning components. The D2K generator automatically constructs a symbolic representation of the features predicted from the unstructured data, and weights such knowledge with a le...