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kl_wgan_sim

kronecker-attention-pytorch

Implementation of Kronecker Attention in Pytorch

ksddescent

Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities

l2hmc

TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network

l2hmc-1

ICLR 2018 Reproducibility Challenge: Generalizing Hamiltonian Monte Carlo with Neural Networks

langevin-dynamics-and-score-matching

A demo shows how to combine Langevin dynamics with score matching for generative models.

langevin-monte-carlo

A simple pytorch implementation of Langevin Monte Carlo algorithms.

lasagne-vae

Variational-autoencoder notebooks and code in Lasagne

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

learn-nlp-with-transformers

we want to create a repo to illustrate usage of transformers in chinese

learnergy

💡 Learnergy is a Python library for energy-based machine learning models.

learning-by-teaching

Learning Implicit Generative Models by Teaching Explicit Ones

lecun1989-repro

Reproducing Yann LeCun 1989 paper "Backpropagation Applied to Handwritten Zip Code Recognition", to my knowledge the earliest real-world application of a neural net trained with backpropagation.

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

lightgbm-with-focal-loss

An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems

lightweight-gan

Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two

likelihood-regret

Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020

logitnorm_ood

Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization

long-tailed-ood-detection

Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (ICML'22 Long Presentation)

lsd

Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"

lsgm

The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)

lwjopt

optimization algorithms library

ma-ebm

Implementation for experiments in Master Thesis.

machine-learning-book

Code Repository for Machine Learning with PyTorch and Scikit-Learn

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

manifold-flow

Manifold-learning flows (ℳ-flows)

marginaltailadaptiveflow

Marginal Tail-Adaptive Normalizing Flows [ICML 2022] https://arxiv.org/abs/2206.10311

mcd_da

mcvae