gnn-lspe
gansformer
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| gnn-lspe | gansformer | |
|---|---|---|
| 3 | 7 | |
| 214 | 1,302 | |
| - | - | |
| 0.0 | 1.8 | |
| about 2 years ago | almost 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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gnn-lspe
- [D] Machine Learning - WAYR (What Are You Reading) - Week 128
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[R] Graph Neural Networks with Learnable Structural and Positional Representations
Code for https://arxiv.org/abs/2110.07875 found: https://github.com/vijaydwivedi75/gnn-lspe
gansformer
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[D] GANs + Transformer = SOTA compositional generator? Compositional Transformers for Scene Generation explained (5-minute summary by Casual GAN Papers)
Code for https://arxiv.org/abs/2111.08960 found: https://github.com/dorarad/gansformer
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Generative Adversarial Transformers [R]
As for whether the Ys are shared across layers, check the code.
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[Project] These players does not exist
I tested the gansformer (https://github.com/dorarad/gansformer) to generate football player faces. Here are some selected results (actually some of the images are real players):
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GANsformers: Scene Generation with Generative Adversarial Transformers š„
References: Paperāŗ: https://arxiv.org/pdf/2103.01209.pdf Codeāŗ: https://github.com/dorarad/gansformer Complete referenceāŗ: Drew A. Hudson and C. Lawrence Zitnick, Generative Adversarial Transformers, (2021), Published on Arxiv.
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[R] Generative Adversarial Transformers (2103.01209)
https://github.com/dorarad/gansformer/blob/148f72964219f8ead2621204bc5cfa89200b6879/training/network.py#L461
What are some alternatives?
pytorch_geometric - Graph Neural Network Library for PyTorch
pytorch-generative - Easy generative modeling in PyTorch.
pna - Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
SteganoGAN - SteganoGAN is a tool for creating steganographic images using adversarial training.
PDN - The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - [ECCV 2022] Compositional Generation using Diffusion Models
efficient-gnns - Code and resources on scalable and efficient Graph Neural Networks
data-efficient-gans - [NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
graphtransformer - Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
long-range-arena - Long Range Arena for Benchmarking Efficient Transformers
gnn - TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
icl-ceil - [ICML 2023] Code for our paper āCompositional Exemplars for In-context Learningā.