A PyTorch implementation of multimodal VRNN and VAE.
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Updated
Sep 6, 2024 - Python
A PyTorch implementation of multimodal VRNN and VAE.
TRGAN: A Time-Dependent Generative Adversarial Network for Synthetic Transactional Data Generation
A PyTorch implementation of various deep generative models, including Diffusion (DDPM), GAN, cGAN, and VAE.
[ICLR 2022] Denoising Likelihood Score Matching for Conditional Score-based Data Generation
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.
Official PyTorch implementation of "Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis" (ICML 2024).
[NeurIPS 2023] VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation
Forward-backward conditional sampling
TRGAN: A Time-Dependent Generative Adversarial Network for Synthetic Transactional Data 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).
ACL'2023: DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
[ICLR 2022] Toy Experiments for Denoising Likelihood Score Matching for Conditional Score-based Data Generation
Code for "Optimal Transport-Guided Conditional Score-Based Diffusion Model (NeurIPS, 8,7,7,6)"
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.
Repository for the paper: 'Diffusion-based Conditional ECG Generation with Structured State Space Models'
Conditional Generative Adversarial Network for Molecular Dynamics frame generation
Few-Shot Diffusion Models
Code for the paper "FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery", published on SDM 2022.
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
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