Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Data can be represented as a vector in a continuous space, but often it is concentrated in a narrow area. Can it be improved?
DeepNightLearners
DeepNightLearners is a series of summaries in the field of deep learning
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration
Augmenting images training data to add variability doesn't always end well since the augmentation changes the semantic content of the image. Here's how to solve it.
Highly accurate protein structure prediction with AlphaFold
AlphaFold2 is the strongest tool today to predict protein 3D structure. It will be massively used to bring the world protein research forward. Since it is very complex and contains many new architectures, in this post, we gradually decompose the system into its base components.
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
This paper suggests a new computationally efficient method for constructing low-dimensional representation of unlabeled data.
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
A review and clear explanation of the NeRF method, which can be used to synthesize 3D scenes out of an input image. This method is the base for many other research methods that followed.