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This paper reviews the mathematical basis of maximum likelihood. The likelihood function for macromolecular structures is extended to include prior phase information and experimental standard uncertainties. The assumptio...

Subjects / keywords: Computer science; Mathematics; Set theory; Problems, exercises, etc; Algorithms; Logic, Symbolic and mathematical; Problems and exercises; Electronic books

Subjects / keywords: Docking (animal); Protein–ligand docking; Searching the conformational space for docking; Ligand (biochemistry); DOCK; Computer science; Flexibility (engineering); Algorithm; Macromolecule; Molecular dynamics; Chemistr...

In this article, we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of th...

A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of "no free lunch" (NFL) theorems are presented which establish that for any algori...

Subjects / keywords: Boosting (machine learning); Multiplicative function; Bounded function; Computer science; Generalization; Mathematical optimization; Decision rule; Artificial intelligence; Mathematics; Machine learning; Algorithm; Mathe...

In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up ...

Subjects / keywords: Feature selection; Artificial intelligence; Selection (genetic algorithm); Computer science; Feature (linguistics); Pattern recognition (psychology); Machine learning; Linguistics; Philosophy

Subjects / keywords: Diffraction; Computer science; Data reduction; Detector; Algorithm; Visualization; Bayesian probability; Data processing; Data mining; Optics; Physics; Artificial intelligence

Subjects / keywords: TREMBLAY, JEAN-PAUL; MCGRAW-HILL; 005.113 T789in

Subjects / keywords: Python (Computer program language); Data structures (Computer science); Computer algorithms

Subjects / keywords: Text processing (Computer science); Genetic algorithms; Computational linguistics

Subjects / keywords: Computer algorithms; Databases; Data structures (Computer science); Structured programming

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial ...

We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression. Taking a pattern classification approach, we consider each pixel in an image as a coordinate in...

The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permi...

Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We briefly review Hochreiter's (1991) analysis of t...