Kyeongwon Lee's Projects
A tutorial about Gaussian process regression
Gaussian processes in TensorFlow
GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
What scientific programmers must know about CPUs and RAM to write fast code.
My first repository on GitHub!
Preview, create PDFs, and print documents in your own style with templates in iA Writer.
This is the Julia Tutorial series
π€ Korean Comments ELECTRA: νκ΅μ΄ λκΈλ‘ νμ΅ν ELECTRA λͺ¨λΈ
Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
kw-lee's blog
A pytorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"
Implement NUTS algorithm using Rcpp
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
Are you an early π€ or a night π¦? Let's check out in gist
Deep Gaussian Processes in Python
Bayesian Deep Learning with Stochastic Gradient MCMC Methods
Tensors and Dynamic neural networks in Python with strong GPU acceleration
95.16% on CIFAR10 with PyTorch
PyTorch implementation of Diffusion Convolutional Recurrent Neural Network
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. [IN PROGRESS]
Deep Learning Zero to All - Pytorch