networked, stochastic SIRD epidemiological model with Bayesian parameter estimation and policy scenario comparison tools
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Jul 25, 2023 - Python
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networked, stochastic SIRD epidemiological model with Bayesian parameter estimation and policy scenario comparison tools
Coursework, projects, and datasets from the MSc in Financial Engineering (MScFE) program at WorldQuant University.
A real-time traffic simulation system for all the cities that models vehicle movement using AI agents, dynamic routing, and environmental factors like congestion and weather
Repository for Pachter Lab Biophysics
Hydrological Model (Berkeley). This project implements the underground (stochastic) hydrological model (in Python) that was developed during my postdoctoral tenure at the Dept. of Earth & Planetary Science, U. C. Berkeley, (2013 - 2016).
Models that are, or will be, featured on Physics of Risk blog.
A decision model build using probability and stochastic process knowledge to mitigate the revenue loss of a company due to unfavorable fluctuations in international Dollar value
heavytails is a Python library implementing heavy-tailed probability distributions, built from first principles with NumPy-backed vectorized evaluation. The library provides comprehensive support for continuous and discrete heavy-tailed distributions, tail index estimation methods, and diagnostic utilities
Source files used to generate Physics of Risk website.
Software for generating one-day synthetic solar irradiance sequences at a minimum 60-minute time resolution.
美国大学生数学建模竞赛:B题 Journey to the Rescue: Submersibles in the Deep Sea
Python version of ANTI-FASc
Code repository for the paper "Stochastic 3D Modelling of Discrete Sediment Bodies for Geotechnical Applications" by G.H. Erharter, F. Tschuchnigg and G. Poscher
Proyek ini menganalisis kinerja sistem antrian di Kantin GKU‑2 ITERA menggunakan pendekatan teori antrian (M/M/1 & M/M/2) untuk memahami pola kedatangan pelanggan, waktu pelayanan, dan dampaknya terhadap durasi tunggu
Queueing Theory and Markov Chain cases, where Stochastic Modeling is applied
Aethel is a high-performance, actuarial-grade Economic Scenario Generator (ESG) in Python, simulating correlated stochastic paths for equities, interest rates, and inflation to support ALM and portfolio decumulation analysis.
Pricing energy options (focus on German power) with MC and jump-diffusion mean-reversion model, including stochastic volatility, seasonality and regime filtering. Model parameters are calibrated on historical ENTSO-e data.
Using a probabilistic approach to simulate a real-life tontine
Forecast short-horizon catalog attention on item graphs using CTMC + Wasserstein drift–diffusion (Retailrocket).
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