PyTorch Implementation of Make-An-Audio (ICML'23) with a Text-to-Audio Generative Model
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Updated
May 22, 2024 - Python
PyTorch Implementation of Make-An-Audio (ICML'23) with a Text-to-Audio Generative Model
Autoencoders in Keras
Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
Latent web browser
Official pytorch implementation of the paper: "An Edit Friendly DDPM Noise Space: Inversion and Manipulations". CVPR 2024.
Code accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"
Codebase for performing various experiments with Stable Diffusion, supported by the diffusers library.
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
ComfyUI extension for advanced manipulation with latent
PyTorch Implementation for the paper "C3VQG: Category Consistent Cyclic Visual Question Generation" (ACM MM Asia'20).
Learning and controlling the source-filter representation of speech with a variational autoencoder
Buckle up, adventure in the styleGAN2-ada-pytorch network latent space awaits
Count{down, up} with MNIST using Latent Interpolation
CVPR 2021, Smoothing the Disentangled Latent Style Space for Unsupervised I2I Translation
LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA accuracy
Official PyTorch implementation of the paper: Flow Matching in Latent Space
A deep learning architecture for robust inference and accurate prediction of cellular dynamics
Controllable Face Generation via pretrained Conditional Adversarial Latent Autoencoder (ALAE)
Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
AI that generates human faces which have never been seen before. The future is now 😁
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