mapleyustat,github

ising_hypercube

A Monte Carlo implementation of the Ising Hamiltonian on a hypercube of arbitrary dimension

krylov-cpp

Time-evolution of a wavefunction using a Krylov subspace expansion

ksresamp

An R package which implements high dimensional kernel smoothing specifically targetted for analyzing diffusion tensor imaging data. It provides various resampling based hypothesis testing tools.

lab-pub

The relationship of the spectral dimension and spatial search on a fractal lattice using quantum walk

lattice-gauge-theory-and-tensor-networks

This is a project aimed at constructing gauge-invariant tensor networks for lattice gauge theory with a view to obtaining a continuous ground-state ansatz for pure Yang-Mills theory.

lawa-phd-skestler

Source files for the PhD thesis "On the Adaptive Tensor Product Wavelet Galerkin Method with Applications in Finance" by Sebastian Kestler

learning-wordnet

Learning wordnet using tensor neural network

levy-flight-random-walk

Levy flight random walk implemented in Processing (p5.js)

Library for reading and writing darx files. A darx (short for data archive) file is a set of data tensors, associated with some archive metadata. Each tensor specifies it's own dimensions and datatype. The purpose of such a file is to store associated data of any type into one single archive. Each tensor's data can be compressed individually, allowing the header to still be read. Also, the format provides built in support for tensors holding mixed and custom data types. The mixed data type specifies elements as a tuple of elements, each with it's own recursively defined data type, whereas the custom data type specifies an application-dependent formatting of the data. Originally created to support bundling of related matrices in one convenient file.

libgpuarray

Library to manipulate tensors on the GPU.

ligost

Scalar-tensor

lindblad

Quantum optical master equation simulations

lindbladsolver

Solves a differential master equation containing operators in Lindblad-Form. Used to simulate open quantum systems.

linear-tensor-interpolation

Linear tensor interpolation in Matlab

logiclda

Fork to make code work directly from repository again until required modules are available from original author. Topic modeling with first-order logic (FOL) domain knowledge

lowrank-stat-matching

Trying to classify state legal statute hierarchies using low-rank tensor methods [forked]

lrslibrary

Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos

ma_visualization

Processing and visualization of datasets used for middle-atmosphere research

main_core_retention

Single document keyphrase extraction by k-core graph decomposition

matrix-entropy

Python implementation of "Measuring entropy/ information/ patterns of a 2d binary matrix" based on the corresponding StackOverflow answer

maximal_independent_set

STXXL implementaion of the same.

mcmc-plus-tensor

R code, simulated data etc for Robinson and Beckerman 2013 Ecology Letters Tensor Based Analysis of Phenotypic Plasticity (Ageing and Population Gradients too).

mcmc-slime-mold

Markov Chain Monte Carlo / Cellular Potts slime mold simulation in JavaScript

mcrn-da

This project involves developing reduced physical and data models and algorithms for data assimilation. The goal of the project is to address computational challenges in data assimilation of dimensionality and non-Gaussian behavior for model problems and relevant small to medium scale problems. This includes a models from many different possible areas: atmosphere, ocean, combined atmosphere/ocean, ice sheet, glacier, hurricane, ENSO, polar vortex, ecological models, etc.. The basic idea is to create computational conceptual models, both physical and data models, and combine these with standard data assimilation techniques and new techniques developed to take advantage of the structure of these conceptual models. Among the data assimilation techniques to be considered are projected particle filters. Focus is on application to problems with bimodal or multimodal behavior which ties in with work on tipping points. Another emphasis is on applying these techniques to higher dimensional problems to create lower dimensional computational conceptual models. The project involves employing, developing, and applying projected data assimilation techniques, in particular projected particle filters, using the framework developed in (Maclean, VV 2019), while focusing on the use of different state space and observation space projections for increasingly high dimensional models.

minerva

Minerva: a fast and flexible tool for deep learning. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy. Please refer to the examples to see how multi-GPU setting is used.

minibook-code

Recipes of the IPython Minibook

mining-the-social-web-2nd-edition

The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)

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