A discrete-time Python-based solver for the Stochastic On-Time Arrival routing problem
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Jan 1, 2022 - Python
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A discrete-time Python-based solver for the Stochastic On-Time Arrival routing problem
Set of Jupyter (iPython) notebooks (and few pdf-presentations) about things that I am interested on, like Computer Science, Statistics and Machine-Learning, Artificial Intelligence (AI), Financial Engineering, Optimization, Stochastic Modelling, Time-Series forecasting, Science in general... and more.
Stochastic SIR models; adding age-structures and social contact data for the spread of covid-19. Lattice model for identifying and isolating hotspots. This has been further developed into a network(graph) of multiple clusters(lattices) and tracing the infection in such a population.
3rd Annual Undergraduate Quantitative Biology (UQ-bio) Summer School
Classical models implemented from a Markov operator's perspective
QuantCore.Net is a high-performance .NET library for quantitative finance computations with low latency,deterministic behavior,and allocation-aware APIs.
Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.
Weather Generators with Bayesian Networks
Adaptive Signal Processing (2020 Fall)
Code and data files necessary for reproducing cellular-automaton model of human spread across Sahul
Modeling of Time-varying Wireless Communication Channel with Fading and Shadowing
Bayesian inference of stochastic cellular processes with and without memory in Python.
Application of the ARIMA model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.
A self-calibrating Monte Carlo simulation engine for stock and options pricing. Pulls real market data, estimates model parameters automatically, prices options under multiple stochastic models, computes risk metrics, and tracks every run via MLflow. Exposed through a FastAPI backend and a React dashboard.
Application of the ETS model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahwalnagar District, Punjab, Pakistan.
This repository contains codes developed in 2022 to simulate the biofilm formation with the proposed stochastic model based on quorum sensing and chemical reactions.
Climate-augmented mortality framework for life insurance — Lee-Carter/CBD models, NGFS scenarios, and Solvency II impacts across Italy, France, Germany & NL
This script presents a simple stochastic description to model cell population distribution in the phases of the cell cycle
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