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Simulation and inference for contextual and neural SBMs
βοΈ spring-boot learning
Focused Python library for slack-based DEA, undesirable outputs, environmental frontiers, and panel productivity analysis.
Analysis of the global trade network for 2018, 2020, and 2022 using network theory, Exponential Random Graph Models (ERGM), and Stochastic Block Models. Non-structural, persistent, and statistically significant nodal determinants of international trade are identified, as well as a marked differentiation between countries.
Catalog-independent Wflow SBM hydrological model for the Upper Niger Basin. Complete ETL pipeline from raw ERA5/SRTM to runnable Julia simulation. Includes documented error resolutions and reusable patterns for building Wflow-sbm model.
Source code of "Semi-Supervised Clustering with Inaccurate Pairwise Annotations" (Gribel, Gendreau and Vidal, 2021)
Source code of AC-DC-SBM, from "Assortative-Constrained Stochastic Block Models" (Gribel, Vidal and Gendreau, 2020)
Space Breakdown Method (SBM) is a clustering algorithm developed for Spike Sorting handling overlapping and imbalanced data. Improved Space Breakdown Method (ISBM) is the updated and improved version of SBM. A new algorithm for the detection of brain oscillations packets has been developed based on SBM, called Time-Frequency Breakdown Method (TFBM)
a python implementation of the standard and super-efficiency SBM (Slack-Based Measure) models, with and without undesirable outputs
Small utility to calculate the robustness modularity, information modularity and modularity difference.
C++ implementation of a MCMC sampler for the (canonical) SBM
A package to sample and estimate variants of the stochastic blockmodel from network data
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