simclr VS deepmind-research

For visual representations, you could look into SimCLR and MoCo. https://github.com/google-research/simclr https://github.com/facebookresearch/moco

Yeah I think so, it's not hard to check https://github.com/google-research/simclr/blob/2fc637bdd6a723130db91b377ac15151e01e4fc2/data_util.py

Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr

SimCLR v2.0 - https://arxiv.org/abs/2006.10029

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.

No, go to the "tf2" folder in the repo root. https://github.com/google-research/simclr/tree/master/tf2

Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr

[1] https://github.com/google-research/simclr [2] https://www.tensorflow.org/tfrc?hl=en&authuser=2

Deepmind 63

Found some here and here.

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.

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.

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

Github: https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21

BYOL - again, it seems that it's not optimized for running on multiple GPUs.