mhashemi0873
Postdoc at Institut de Neuroscience des Systèmes, Marseille. Bayesian inference, Brain dynamics, AI/ML, MCMC.
Marseille France
Pinned Repositories
BVEP
The Bayesian Virtual Epileptic Patient: a probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread
Epileptor2D
EpileptorParameterInference
ForecastingTimeSeries
Graph-Stochastic-Wilson-Cowan-Model
Analytic results and numerical simulations for a (connectome) graph-based Wilson-Cowan stochastic neural field model
Inference_MFM
Inference on a mean-field model of spiking neurons
PPCA
Probabilistic PCA
sbi
Simulation-based inference toolkit
SpectralPowerFitting
Optimal Model Parameter Estimation From EEG Power Spectrum Features Observed During General Anesthesia, Hashemi et al, Neuroinformatics 2018
stan
Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
TVB-tutorial
mhashemi0873's Repositories
mhashemi0873/Epileptor2D
EpileptorParameterInference
mhashemi0873/Inference_MFM
Inference on a mean-field model of spiking neurons
mhashemi0873/PPCA
Probabilistic PCA
mhashemi0873/TVB-tutorial
mhashemi0873/BVEP
The Bayesian Virtual Epileptic Patient: a probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread
mhashemi0873/ForecastingTimeSeries
mhashemi0873/stan
Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
mhashemi0873/abcpy
ABCpy package
mhashemi0873/awesome-neural-sbi
Community-sourced list of papers and resources on neural simulation-based inference.
mhashemi0873/BAP
Bayesian Analysis with Python (Second Edition)
mhashemi0873/bayescogsci
Draft of book entitled An Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, Vasishth
mhashemi0873/BayesFlow
A Python library for amortized Bayesian workflows using generative neural networks.
mhashemi0873/Bayesian_Optimization
Bayesian Optimization to find the global min/max of a black box function.
mhashemi0873/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
mhashemi0873/botorch
Bayesian optimization in PyTorch
mhashemi0873/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
mhashemi0873/dynamax
State Space Models library in JAX
mhashemi0873/flowMC
Normalizing-flow enhanced sampling package for probabilistic inference in Jax
mhashemi0873/GPflow
Gaussian processes in TensorFlow
mhashemi0873/neurolib
Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿🔬
mhashemi0873/normalizing-flows
PyTorch implementation of normalizing flow models
mhashemi0873/PCNtoolkit
Toolbox for normative modelling and spatial inference of neuroimaging data. https://pcntoolkit.readthedocs.io/en/latest/
mhashemi0873/personalwebpage
This is my webpage.
mhashemi0873/PolynomialModelComparision
mhashemi0873/pysindy
A package for the sparse identification of nonlinear dynamical systems from data
mhashemi0873/pytorch-Deep-Learning
Deep Learning (with PyTorch)
mhashemi0873/scikit-optimize
Sequential model-based optimization with a `scipy.optimize` interface
mhashemi0873/SourceEstimation
SEEG Source Localization
mhashemi0873/tutorial-sampling-enhanced-w-generative-models
mhashemi0873/uvadlc_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022