Uncertainty Quantification for Physical and Biological Models
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Updated
Jan 11, 2023 - MATLAB
Uncertainty Quantification for Physical and Biological Models
Final Assignment for Maastricht University EBS 2072: Introduction to Software in Econometrics
Gibbs samplers for inferring latent variables and learning the parameters of Bayesian hierarchical models.
AI Repository
Unsupervised learning , iteration algorithm, and data generation in Frequentist And Bayesian inferences.
Running Monte Carlo - Markov Chain algorithm on synthesized spectral models made by CLOUDY to compare them with data from CECILIA survey
A Python API for Bayesian Generalised Linear Models.
Approximate Bayesian Computation algorithm based on simulated annealing
Code the ICML 2024 paper: "EMC^2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence"
The repository houses the source code of paper
Code used to constrain dark matter substructure in the solar neighborhood with Gaia eDR3 wide binaries.
A few proofs and examples related to ML/Prob and Optimisation
Cuadernos introductorios
Adaptive paralelle tempering for sampling multi-modal posteriors in NIMBLE.
Python package for retrieval of properties of exoplanets by model-fitting their transit light curves using MCMC with additional features such as detrending of light curves, GP regression, and continuous monitoring of the retrieval process.
Implementation of Markov chain Monte Carlo sampling and the Metropolis-Hastings algorithm for multi-parameter Bayesian inference.
Some interesting applications of Stochastic Processes using Jupyter Notebooks for descriptive and instructive illustrations.
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