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  2. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    The classical finite-difference approximations for numerical differentiation are ill-conditioned. However, if is a holomorphic function, real-valued on the real line, which can be evaluated at points in the complex plane near , then there are stable methods.

  3. Mathematics - Wikipedia

    en.wikipedia.org/wiki/Mathematics

    The word mathematics comes from the Ancient Greek word máthēma (μάθημα), meaning ' something learned, knowledge, mathematics ', and the derived expression mathēmatikḗ tékhnē (μαθηματικὴ τέχνη), meaning ' mathematical science '. It entered the English language during the Late Middle English period through French and ...

  4. Large numbers - Wikipedia

    en.wikipedia.org/wiki/Large_numbers

    A natural language numbering system allows for representing large numbers using names that more clearly distinguish numeric scale than a series of digits. For example "billion" may be easier to comprehend for some readers than "1,000,000,000".

  5. Infix notation - Wikipedia

    en.wikipedia.org/wiki/Infix_notation

    Binary relations are often denoted by an infix symbol such as set membership a ∈ A when the set A has a for an element. In geometry, perpendicular lines a and b are denoted , and in projective geometry two points b and c are in perspective when while they are connected by a projectivity when .

  6. Numerical range - Wikipedia

    en.wikipedia.org/wiki/Numerical_range

    In engineering, numerical ranges are used as a rough estimate of eigenvalues of A. Recently, generalizations of the numerical range are used to study quantum computing. A related concept is the numerical radius, which is the largest absolute value of the numbers in the numerical range, i.e.

  7. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Beyond their traditional applications, artificial neural networks are increasingly being utilized in interdisciplinary research, such as materials science. For instance, graph neural networks (GNNs) have demonstrated their capability in scaling deep learning for the discovery of new stable materials by efficiently predicting the total energy of ...