Clustering users into different groups based on click logs of news articles
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Updated
Mar 23, 2018 - Python
Clustering users into different groups based on click logs of news articles
PyTorch implementation of Bayesian Graph Convolutional Networks using Neighborhood Random Walk Sampling to supplement my Honors Thesis.
Implementation of neural coherent states, arXiv:2105.15193
This repo implements Robert, Wu, Stoehr, CP Robert - 2019 (https://arxiv.org/abs/1810.04449) algorithms eHMC and prHMC
Monte Carlo Markov Chain sampler for a given function
This repo is for the code written for the Computational Lab at University of Pisa. This is a work in progress, the main topic will be the implementation of the Propp-Wilson for the study of the Ising model.
Repository for my research project on Inverse Contextual Bandits
Sujet de grand oral en maths, ce programme python permet de calculer la probabilité de chaque case du jeu Monopoly en utilisant les chaines de Markov et la méthode de Monte Carlo
This is a python package based on the source code for "An MCMC Based Course to Teaching Assistant Allocation", S. Kumar, S. Moothedath, P. Chaporkar, M. Belur, Proceedings of the Fifth International Conference on Network, Communication and Computing (2016). ACM.
Generating Neural Spatial Interaction Tables
Source code for the paper "An MCMC based course to teaching assistant allocation".
A library which trains the Fermionic Neural Network to find the ground state wave functions of an atom or a molecule using neural network quantum states.
Graph-theoretical cluster algorithm for clusters of directly connected hard spheres. Sampling based on a Markov-Chain-Monte-Carlo method.
Estimate experimental error rates from replicates using MCMC.
Finding a cure through using Python libraries and dependencies for support.
Python implementation of the cellular automata model corresponding to Lange, Schmied et. al.
MDP and Monte Carlo solution for maze solving
AI projects on: minimax algorithm, variations of nqueens problem, and policy iteration in Markov Decision Processes
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