deepmind-research
Pytorch
deepmind-research | Pytorch | |
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29 | 340 | |
12,817 | 78,016 | |
0.8% | 1.4% | |
0.6 | 10.0 | |
2 days ago | 6 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | BSD 1-Clause 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.
Pytorch
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Clasificador de imágenes con una red neuronal convolucional (CNN)
PyTorch (https://pytorch.org/)
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AI enthusiasm #9 - A multilingual chatbot📣🈸
torch is a package to manage tensors and dynamic neural networks in python (GitHub)
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
What are some alternatives?
jaxline
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
dm-haiku - JAX-based neural network library
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
flax - Flax is a neural network library for JAX that is designed for flexibility.
alphafold_pytorch - An implementation of the DeepMind's AlphaFold based on PyTorch for research
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
swav - PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more