EQTransformer
Perceiver
| EQTransformer | Perceiver | |
|---|---|---|
| 1 | 7 | |
| 330 | 87 | |
| 1.5% | - | |
| 3.2 | 2.6 | |
| 9 months ago | almost 4 years ago | |
| Python | Python | |
| MIT License | MIT License |
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EQTransformer
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An Unethical Question
Here is a specific idea that would be interesting to test. SCITS released a ML P&S picker that supposedly is pretty good. They put the code on github (https://github.com/smousavi05/EQTransformer). I think a really easy idea would be to put it to the test against USGS picks in different areas. You can get IRIS data and run this in a different area that doesn't normally get much attention and see how it compares to the published catalog. Software like this always makes bold claims, so it would be nice to have independent, verified tests of it. You would just need to download the package (it's already on pypi so you can pip it), learn how to run it, and test against some real data. Would make for a decent paper actually.
Perceiver
- I implemented Deepmind's new Perceiver Model
- I Implemented Deepmind's Perceiver Model
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[P] I implemented DeepMind's "Perceiver" in PyTorch
Great one, I implemented the Perceiver model too in TensorFlow: https://github.com/Rishit-dagli/Perceiver
- Deepmind's New Perceiver Model
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[P] Implementing Perceiver: General perception with Iterative Attention in TensorFlow
The project: https://github.com/Rishit-dagli/Perceiver
- Perceiver, General Perception with Iterative Attention
What are some alternatives?
paraphraser - Sentence paraphrase generation at the sentence level
deepmind-perceiver - My implementation of DeepMind's Perceiver
enformer-pytorch - Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
PCGrad - Code for "Gradient Surgery for Multi-Task Learning"
Fast-Transformer - An implementation of Additive Attention
x-transformers - A concise but complete full-attention transformer with a set of promising experimental features from various papers
performer-pytorch - An implementation of Performer, a linear attention-based transformer, in Pytorch
RWKV-LM - RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
TimeSformer-pytorch - Implementation of TimeSformer from Facebook AI, a pure attention-based solution for video classification
CrabNet - Predict materials properties using only the composition information!