This repository contains projects related to various aspects of image processing, from basic operations to advanced techniques like active contours. Examples and case studies focus on applications in medical imaging.

Source code for the evaluated benchmarks and proposed cache management technique, GRASP, in [Faldu et al., HPCA'20].

Fits a discharge rating curve based on the power-law and the generalized power-law from data on paired water elevation and discharge measurements in a given river using a Bayesian hierarchical model as described in Hrafnkelsson et al. (2022)

Library for rain estimation and detection built with PyTorch. This library provides an implementation of algorithms for extracting rain-rate using data from commercial microwave links (CMLs). Addinaly this project provide an example dataset with data from two CMLs and implementation of performance and robustness metrics

Source code for the evaluated benchmarks and proposed cache management technique, GRASP, in [Faldu et al., HPCA'20].

Source code for the graph reordering technique, DBG, published in [Faldu et al., IISWC'19].

Source code for the graph reordering technique, DBG, published in [Faldu et al., IISWC'19].

Shows the Bitcoin & Kaspa power law price channels

This repository provides MATLAB implementations of plfit and plpva functions for fitting power-law distributions to empirical data using maximum likelihood estimation (MLE) and statistical goodness-of-fit tests. These tools accurately model complex systems with significant tail behaviors, common in fields like physics, biology, and economics.

Solves the Cauchy Momentum equations for a non-newtonian incompressible fluid using the Finite Difference Method on a 2D grid. The solver is of the explicit type with each iteration corresponding to a step forward in time. The viscosity is updated at each grid point as per the truncated power law.

Text Clustering Toolkit for Bayesian Nonparametric Analysis

Create a readable stream for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.

Pareto (Type I) distributed pseudorandom numbers.

Research project that focuses on observing the Resilience of Delhi Road Networks to Traffic Disruptions

Symbolic Regression - Function Discovery

Implementation of Power Law Graph Transformer for Machine Translation and Representation Learning.

Estimate tail parameters of heavy-tailed distributions (including power law exponent gamma) in Python

South-California earthquakes data analysis.

限られた粒径のマイクロプラスチックの実測データに当てはめたべき分布のスケールパラメタ等から、未計測の粒径範囲を含むマイクロプラスチック濃度を推定するための補正係数の計算方法

The idea is to propose several models based on Bayesian inference to estimate the likelihood of certain events in Venture Capital

Create an array containing pseudorandom numbers drawn from a Pareto (Type I) distribution.

A DSL for asserting password composition policy effectiveness.

Hedera & SaucerSwap based BTC/USDC re-balancing robot powered by a Bitcoin heartbeat + power‑law allocation model.

Natural logarithm of the probability density function (PDF) for a Pareto (Type I) distribution.

Pareto distribution (Type I) probability density function (PDF).

Create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.

The project for the course "Web Information Retrieval"

Code and data repository supporting "Power-law scaling relationships link canopy structural complexity and height across forest types."

Demonstrate Zipf's law with Sherlock Holmes' stories

Modified gap statistic (gap-com) for regularization selection of sparse networks. This method is aimed for complex network estimation.