There are 0 repository under conditional-generation topic.
ACL'2023: DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
High-performance Image Tokenizers for VAR and AR
Update-to-data resources for conditional content generation, including human motion generation, image or video generation and editing.
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
This is the official implementation for ControlVAR.
Few-Shot Diffusion Models
Code for "Optimal Transport-Guided Conditional Score-Based Diffusion Model (NeurIPS, 8,7,7,6)"
Repository for the paper: 'Diffusion-based Conditional ECG Generation with Structured State Space Models'
[NeurIPS 2023] VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Controllable Face Generation via pretrained Conditional Adversarial Latent Autoencoder (ALAE)
Official PyTorch implementation of "Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis" (ICML 2024).
A PyTorch implementation of various deep generative models, including Diffusion (DDPM), GAN, cGAN, and VAE.
TRGAN: A Time-Dependent Generative Adversarial Network for Synthetic Transactional Data Generation
[ICLR 2022] Denoising Likelihood Score Matching for Conditional Score-based Data Generation
Controllable Sequence Editing for Counterfactual Generation
Code for the paper "FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery", published on SDM 2022.
[ICLR 2022] Toy Experiments for Denoising Likelihood Score Matching for Conditional Score-based Data Generation
A framework for tabular data generation using GANs, featuring conditional generation and benchmarking tools.
[NeurIPS 2024] Supporting code for the paper 'Diffusion Twigs with Loop Guidance for Conditional Graph Generation'.
TRGAN: A Time-Dependent Generative Adversarial Network for Synthetic Transactional Data Generation
DDPM (Denoising Diffusion Probabilistic Models) and DDIM (Denoising Diffusion Implicit Models) for conditional image generation
A partial pytorch implementation of "Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models" for practice
Diffusion Models crash course with Pytorch from DeepLearningAI
Chinese couplet generation with transformer and simple transformer-based variants.
MSc Thesis on Conditional dMRI Generative AI Models and their applicability in the decreasing scan acquisition times and bettering of patient's quality of life.
The aim of this work is to generate new face images similar to training ones (the CelebA dataset) according to user specified attributes. To do that we ended up with an implementation of a Versatile Auxiliary Classifier + GAN.
Metadata-conditional diffusion model for flexible time-series generation. Model + Analysis
Conditional Generative Adversarial Network for Molecular Dynamics frame generation
A Few-shot Personalized Image Editing model utilizing Stable Diffusion to enable precise image modifications based on textual descriptions and reference images (Course Project).
A PyTorch implementation of multimodal VRNN and VAE.
Fine-Tuning BLIP for Image Captioning A project to fine-tune the BLIP model for generating inspirational captions from images. Includes tools for training, comparing base vs fine-tuned outputs, and visualizing results.