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
Official pytorch implementation of the paper: "An Edit Friendly DDPM Noise Space: Inversion and Manipulations". CVPR 2024.
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Official PyTorch implementation of the paper: Flow Matching in Latent Space
Codebase for performing various experiments with Stable Diffusion, supported by the diffusers library.
Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
Autoencoders in Keras
Implementation of 🥥 Coconut, Chain of Continuous Thought, in Pytorch
Buckle up, adventure in the styleGAN2-ada-pytorch network latent space awaits
A deep learning architecture for robust inference and accurate prediction of cellular dynamics
Code accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"
Learning and controlling the source-filter representation of speech with a variational autoencoder
CVPR 2021, Smoothing the Disentangled Latent Style Space for Unsupervised I2I Translation
3DGANTex: 3D Face Reconstruction with StyleGAN3-based Texture Synthesis from Multi-View Images
GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
Code implementation of the detection network capable of dealing with many overlapping spline bodies.
Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
Remaining Useful Life estimation and sensor data generation by VAE and diffusion model on C-MAPSS dataset.
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'.
LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA accuracy
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