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reproducible-research

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JavierAntoran / Bayesian-Neural-Networks

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Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

deep-learning reproducible-research regression pytorch uncertainty classification uncertainty-neural-networks bayesian-inference mcmc variational-inference hmc bayesian-neural-networks langevin-dynamics approximate-inference local-reparametrization-trick kronecker-factored-approximation mc-dropout bayes-by-backprop out-of-distribution-detection sgld
  • Updated Oct 20, 2023
  • Jupyter Notebook

MaurizioFD / RecSys2019_DeepLearning_Evaluation

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This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

deep-learning neural-network reproducible-research collaborative-filtering matrix-factorization hyperparameters bpr recommendation-system recommender-system reproducibility recommendation-algorithms knn matrix-completion evaluation-framework content-based-recommendation hybrid-recommender-system funksvd bprmf bprslim slimelasticnet
  • Updated May 25, 2023
  • Python

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