Generative Models
Showing 14 of 14 projects
Interactive point-based manipulation tool for editing GAN-generated images by dragging points to target positions.
A collection of concise PyTorch tutorials for deep learning researchers, with most models implemented in under 30 lines of code.
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Original implementation and hyperparameters for the 2014 paper "Generative Adversarial Networks" (GANs).
A curated list of academic papers and resources for image and video inpainting techniques.
A Python package for generating synthetic tabular and time-series data using state-of-the-art generative models like GANs and Gaussian Mixtures.
A benchmarking platform for molecular generation models, providing datasets, implementations, and evaluation metrics for drug discovery research.
A lightweight TensorFlow library for training and evaluating Generative Adversarial Networks (GANs).
TensorFlow implementation of unsupervised cross-domain image generation for transferring images between domains like SVHN to MNIST.
An Emacs org-mode minor mode that integrates generative AI models like ChatGPT, DALL-E, and Stable Diffusion for text and image generation.
A deep learning toolkit for computational chemistry and drug design research with PyTorch backend.
A curated collection of research papers tracking the frontier of AI-based protein design methods and applications.
A JAX library for building, training, and evaluating normalizing flows for probabilistic modeling.
A TensorFlow implementation of Attend, Infer, Repeat (AIR), a generative model for fast scene understanding by reconstructing objects sequentially.
A curated list of 257+ research papers on video generation, representation learning, and related topics like reinforcement learning.
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