Probabilistic inversion within a multiple-point statistics framework is still computationally prohibitive for large-scale problems. To partly address this, we introduce and evaluate a new training-image based simulation and inversion approach for complex geologic media. Our approach relies on a deep neural network of the spatial generative adversarial network (SGAN) type. After training using a...

We propose an approach and a subsequent extension for reversing imperative programs. Firstly, we produce both an augmented version and a corresponding inverted version of the original program. Augmentation saves reversal information into an auxiliary data store, maintaining segregation between this and the program state, while never altering the data store in any other way than that of the orig...

Numerical inversions for earthquake source parameters from tsunami wave data usually incorporate subjective elements to stabilize the search. In addition, noisy and possibly insufficient data result in instability and non-uniqueness in most deterministic inversions, which are barely acknowledged. Here, we employ the satellite altimetry data for the 2004 Sumatra-Andaman tsunami event to invert t...

The inversion method proposed by Glück and Kawabe uses grammar programs as intermediate results that comprise sequences of operations (data generation, matching, etc.). The determinization method used in the inversion method fails for a grammar program of which the collection of item sets causes a conflict even if there exists a deterministic program equivalent to the grammar program. In this p...

The study of genomic inversions (or reversals) has been a mainstay of computational genomics for nearly 20 years. After the initial breakthrough of Hannenhalli and Pevzner, who gave the first polynomial-time algorithm for sorting signed permutations by inversions, improved algorithms have been designed, culminating with an optimal linear-time algorithm for computing the inversion distance and a...

Inversions are used as a fundamental quantity to measure the sortedness of data, to evaluate diierent ranking methods for databases, and in the context of rank aggregation. Considering the volume of the data sets in these applications, the data stream model 16, 2] is a natural setting to design eecient algorithms. We obtain a suite of space-eecient streaming algorithms for approximating the num...

Seismologists have long used extended sources, both physical and synthetic, to enhance the effectiveness of data acquisition and processing in various ways. Recently, extended synthetic sources have been suggested as a means to to substantially reduce the computational complexity of waveform inversion. Most proposed synthetic sources for waveform inversion are random in some way. In contrast, I...

As a sedimentary mineral, most sandstone type uranium deposits are formed in petroliferous basins. Therefore, we can fully tap the residual economic value of historical logging and 3D seismic data measured for oil gas to search deposits. However, large amount acoustic missing target stratum reservoir that it is not main gas. A reconstructed method based on clustering analysis with low-frequency...

We present an inversion algorithm for nonsingular n × n matrices whose entries are degree d polynomials over a field. The algorithm is deterministic and, when n is a power of two, requires O (̃n3d) field operations for a generic input; the soft-O notation O ̃indicates some missing log(nd) factors. Up to such logarithmic factors, this asymptotic complexity is of the same order as the number of dis...

A method is proposed for the calculation of diffusion constants for one-dimensional maps exhibiting deterministic diffusion. The procedure is based on harmonic inversion and uses a known relation between the diffusion constant and the periodic orbits of a map. The method is tested on an example map for which results calculated by different other techniques are available for comparison.  2001 E...