A Collection of Variational Autoencoders (VAE) in PyTorch.
-
Updated
Jun 13, 2024 - Python
A Collection of Variational Autoencoders (VAE) in PyTorch.
Official implementation for the paper: "Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering""
[CVPR2020] Adversarial Latent Autoencoders
an incremental approach to compiler construction
Generative Adversarial Networks implemented in PyTorch and Tensorflow
Attention is all you need implementation
Stable Diffusion implemented from scratch in PyTorch
Knowledge Distillation: CVPR2020 Oral, Revisiting Knowledge Distillation via Label Smoothing Regularization
Knowledge triples extraction and knowledge base construction based on dependency syntax for open domain text.
TensorFlow implementation of Independently Recurrent Neural Networks
Easy generative modeling in PyTorch
📃 𝖀𝖓𝖔𝖋𝖋𝖎𝖈𝖎𝖆𝖑 PyTorch Implementation of DA-RNN (arXiv:1704.02971)
Important paper implementations for Question Answering using PyTorch
Implementation of character based convolutional neural network
[ICLR2024] Official repo for paper "PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code"
LLaMA 2 implemented from scratch in PyTorch
Algorithm implementation for my Edge Computing-related papers.
Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)
Tensorflow implementation of Neural Scene Representation and Rendering
ZeroRF: Fast Sparse View 360° Reconstruction with Zero Pretraining
Add a description, image, and links to the paper-implementations topic page so that developers can more easily learn about it.
To associate your repository with the paper-implementations topic, visit your repo's landing page and select "manage topics."