deepmind-research
TorchPQ
deepmind-research | TorchPQ | |
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29 | 3 | |
12,817 | 203 | |
0.8% | - | |
0.6 | 3.5 | |
2 days ago | 5 months ago | |
Jupyter Notebook | Cuda | |
Apache License 2.0 | MIT License |
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deepmind-research
- This A.I. Subculture's Motto: Go, Go, Go. The eccentric pro-tech movement known as "Effective Accelerationism" wants to unshackle powerful A.I., and party along the way.
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How worried are you about AI taking over music?
Deepmind 63
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Are there Notebooks of AlphaFold 1?
Found some here and here.
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Trying to port this non-standard Tensorflow model to Pytorch and not sure if I'm missing anything
I am trying to make a physics-simulation model based on DeepMind's research, with its source code found here https://github.com/deepmind/deepmind-research/tree/master/learning_to_simulate . The thing that mainly confuses me is how to properly implement the embedding situation found at https://github.com/deepmind/deepmind-research/blob/master/learning_to_simulate/learned_simulator.py on lines 78 and 152.
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[D] Is it possible to use machine learning to create 3D images for the purpose of 3D printing?
Yes. There's a fair bit of research into using ML to generate 3D models. Early work, like Neural Radiance Fields (NeRF) generated a voxel model, which could be used for 3D printing, but it would be low resolution, like blowing up a tiny image vs an SVG vector file. However, more recent research can generate polygonal models from a video taken of a real object. Polygonal models are much better for 3D printing.
- DeepMind Research – code to accompany DeepMind publications
- Skilful precipitation nowcasting using deep generative models of radar - Dr. Piotr Mirowski - Zoom
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[R] Skilful precipitation nowcasting using deep generative models of radar - Link to a free online lecture by the author in comments (deepmind research published in nature)
Skilful precipitation nowcasting using deep generative models of radar https://www.nature.com/articles/s41586-021-03854-z https://deepmind.com/blog/article/nowcasting https://github.com/deepmind/deepmind-research/tree/master/nowcasting
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Deepmind Open-Sources DM21: A Deep Learning Model For Quantum Chemistry
Github: https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21
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[P] Choosing a self-supervised learning framework that's easy to use
BYOL - again, it seems that it's not optimized for running on multiple GPUs.
TorchPQ
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[D] Is there an open-source implementation of the Retrieval-Enhanced Transformer (RETRO)?
if you're decided to run nearest neighbor search on GPU, you might wanna give TorchPQTorchPQ a try
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[P] TorchPQ: Efficient Nearest Neighbor Search and Clustering on GPUs
TorchPQ is a python library for approximate nearest neighbor search on GPUs. It has efficient implementations of IVFPQ algorithm as well as some of its variants (e.g IVFPQ+R). The project is written mostly in python using pytorch library, with some custom CUDA kernels to accelerate clustering, searching and indexing.
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Are there more practical tools for KNN searches and storing documents/embeddings?
If you're using GPU for search, You can give TorchPQ a try, it's an ANN search library implemented with PyTorch and CUDA. with TorchPQ, you can freely add / remove vectors with IDs, you can save/load them just like a regular PyTorch model. TorchPQ is still in development, and I'd love to hear any suggestion or feedback.
What are some alternatives?
jaxline
faiss - A library for efficient similarity search and clustering of dense vectors.
dm-haiku - JAX-based neural network library
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
nmslib - Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
flax - Flax is a neural network library for JAX that is designed for flexibility.
FirstCollisionTimestepRarefiedGasSimulator - This simulator computes all possible intersections for a very small timestep for a particle model
alphafold_pytorch - An implementation of the DeepMind's AlphaFold based on PyTorch for research
Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.
swav - PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
DOKSparse - sparse DOK tensors on GPU, pytorch