Repository | Description | Stats |
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WHAM | Python package to construct free energy profiles from biased molecular simulation data using both log-likelihood maximization and self-consistent iteration approaches. | |
postmetad | Python package for post-processing PLUMED metadynamics and OPES simulations. | |
stringmethod | Python implementation of the string method to compute the minimum energy path between two points on any 2-dimensional energy landscape. | |
pyves | Python package to perform variationally enhanced sampling for single-particle langevin dynamics with neural network bias potentials and path collective variables, using OpenMM + PyTorch. | |
INDUSAnalysis | Python package to analyze molecular simulation data generated using GROMACS-INDUS. | |
bootstrapping_tutorial | Jupyter notebook tutorial on bootstrapping (and other related methods) for resampling and calculating uncertainties from correlated timeseries data. | |
gcmc | C++ code for Markov Chain Monte Carlo simulations in the grand canonical ensemble. |
Repository | Description | Stats |
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paperfetcher | Python package to automate handsearching and citation searching for systematic reviews. | |
paperfetcher-web-app | Streamlit web-app for paperfetcher. | |
paperfetcheR-Notebooks | R-Notebooks demonstrating how to use paperfetcher in R. | |
paperfetcheR-starter | R scripts to help you quickly get started with handsearching and citation searching using paperfetcher. |
Repository | Description | Stats |
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gemini_penn | Unofficial fork of the Gemini beamerposter theme with the University of Pennsylvania logo, colors, and fonts. | |
GameOfLife | Conway's Game of Life on a rectangular 2D grid with OpenMP parallelization. | |
multiagent_timetable_scheduling | Netlogo implementation of a multi-agent based algorithm for solving a simplified version of the University Timetabling Problem, using Simulated Annealing. | |
keras_sklearn_models | tf2/keras deep learning models on image data and sklearn machine learning models on tabular data. | |
torch_models | Deep learning models in PyTorch. |