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stein-variational-gradient-descent

code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

stein-variational-gradient-descent-1

SVGD implementation

stein_discrepancies

Code for Part III Essay on Stein Discrepancies

stochastic_normalizing_flows

Stochastic Normalizing Flows

storywriter

小书匠 markdown 笔记

stylegan_xl

StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

subspace-diffusion

子空间扩散模型

survae_flows

Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"

svgd-pytorch

A PyTorch implementation of SVGD (Stein Variational Gradient Descent), contains all examples including bayesian inference in the paper

svgd-torch

An extensible implementation at a BNN with Stein Variational Gradient Descent

symbolic-music-diffusion

Symbolic Music Generation with Diffusion Models

taming-transformers

Taming Transformers for High-Resolution Image Synthesis

tauldr

team-learning

主要展示Datawhale的组队学习计划。

template-nvae

Simple NVAE implementation intended for effective reuse and learning purposes

temporal-normalizing-flows-for-sdes

Try to approximate the solution of Fokker-Planck equation

tensor2tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

textual_inversion

tfgan_eval_inception_1

tomesd

Speed up Stable Diffusion with this one simple trick!

torch-checkpointing

Compile a torch model to a checkpointed model

torchcde

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

torchdyn

A PyTorch based library for all things neural differential equations and implicit neural models.

torchsde

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

truncated-diffusion-probabilistic-models

Pytorch implementation of TDPM

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

tuning_playbook_zh_cn

一本系统地教你将深度学习模型的性能最大化的战术手册。

twostagevae

umnn

Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.

unbiased_ddpm