deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications (by google-deepmind)
simclr
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners (by google-research)
| deepmind-research | simclr | |
|---|---|---|
| 29 | 13 | |
| 12,817 | 3,933 | |
| 0.8% | 1.0% | |
| 0.6 | 2.9 | |
| 2 days ago | 12 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deepmind-research
Posts with mentions or reviews of deepmind-research.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-03.
- 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.
simclr
Posts with mentions or reviews of simclr.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-25.
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Positive and Negative Sampling Strategies for Representation Learning in Semantic Search
For visual representations, you could look into SimCLR and MoCo. https://github.com/google-research/simclr https://github.com/facebookresearch/moco
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[D] Why is random cropping necessary in SimCLR?
Yeah I think so, it's not hard to check https://github.com/google-research/simclr/blob/2fc637bdd6a723130db91b377ac15151e01e4fc2/data_util.py
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[R] Deep Learning with a Small Training Batch (or Lack Thereof). Part 1
Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr
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[D] Current trends in computer vision related to unsupervised learning
SimCLR v2.0 - https://arxiv.org/abs/2006.10029
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Self-Supervised Contrastive Learning model for video dataset?
My data consists of binary labels (normal & anomalous) where the videos are already broken up into frames in the directory, I'm looking for a model where I can feed a normal-labeled video alongside an anomalous-labeled video like visualized in this example from the SimCLR Repo, a dog will represent the normal video and the chair the anomalous video.
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[P] Choosing a self-supervised learning framework that's easy to use
No, go to the "tf2" folder in the repo root. https://github.com/google-research/simclr/tree/master/tf2
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[D] What is meant by width in the SimCLRv2 paper?
Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr
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[D] Funding PhD in Europe
[1] https://github.com/google-research/simclr [2] https://www.tensorflow.org/tfrc?hl=en&authuser=2
What are some alternatives?
When comparing deepmind-research and simclr you can also consider the following projects:
jaxline
swav - PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
dm-haiku - JAX-based neural network library
Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
flax - Flax is a neural network library for JAX that is designed for flexibility.
SimCLR - PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
alphafold_pytorch - An implementation of the DeepMind's AlphaFold based on PyTorch for research
torchlars - A LARS implementation in PyTorch
Supervised-Constrastive-Learning-in-TensorFlow-2 - Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al. [Moved to: https://github.com/sayakpaul/Supervised-Contrastive-Learning-in-TensorFlow-2]
deepmind-research vs jaxline
simclr vs swav
deepmind-research vs dm-haiku
simclr vs Unsupervised-Classification
deepmind-research vs RETRO-pytorch
simclr vs unsupervised-depth-completion-visual-inertial-odometry
deepmind-research vs flax
simclr vs SimCLR
deepmind-research vs alphafold_pytorch
simclr vs torchlars
deepmind-research vs swav
simclr vs Supervised-Constrastive-Learning-in-TensorFlow-2