Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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D2l En | 20,613 | 3 months ago | 2 | November 13, 2022 | 115 | other | Python | |||
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. | ||||||||||
Gpytorch | 3,337 | 4 | 79 | 3 months ago | 38 | June 02, 2023 | 343 | mit | Python | |
A highly efficient implementation of Gaussian Processes in PyTorch | ||||||||||
Deep Kernel Transfer | 142 | 2 years ago | 6 | Python | ||||||
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020) | ||||||||||
Data Efficient Reinforcement Learning With Probabilistic Model Predictive Control | 76 | a year ago | mit | Python | ||||||
Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments | ||||||||||
Random Fourier Features | 66 | 5 months ago | mit | Python | ||||||
Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model | ||||||||||
Candlegp | 59 | 4 years ago | apache-2.0 | Jupyter Notebook | ||||||
Gaussian Processes in Pytorch | ||||||||||
Pytorch Minimal Gaussian Process | 38 | a year ago | Jupyter Notebook | |||||||
A minimal implementation of Gaussian process regression in PyTorch | ||||||||||
Gp | 14 | 6 years ago | mit | Python | ||||||
Differentiable Gaussian Process implementation for PyTorch | ||||||||||
Gptools | 12 | 7 months ago | 4 | bsd-3-clause | Python | |||||
Gaussian processes on graphs and lattices in Stan and pytorch. | ||||||||||
Gp_drf | 11 | 5 years ago | 3 | Python | ||||||
Official code for "Efficient Deep Gaussian Process Models for Variable-Sized Inputs" - accepted in IJCNN2019 |