1 citations · 1 across the 5 of their papers we have counts for
5 papers
Inverting Non-Injective Functions with Twin Neural Network Regression
Sebastian J. Wetzel
Non-injective functions are not globally invertible. However, they can often be restricted to locally injective subdomains where the inversion is well-defined. In many settings a p…
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel, Seungwoong Ha, Raban Iten +2
Machine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulatio…
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients
Sebastian J. Wetzel, Zakaria Patel
It has been demonstrated that artificial neural networks like autoencoders or Siamese networks encode meaningful concepts in their latent spaces. However, there does not exist a co…
Closed-Form Interpretation of Neural Network Classifiers with Symbolic Gradients
Sebastian Johann Wetzel
I introduce a unified framework for finding a closed-form interpretation of any single neuron in an artificial neural network. Using this framework I demonstrate how to interpret n…
Twin Neural Network Improved k-Nearest Neighbor Regression
Sebastian J. Wetzel
Twin neural network regression is trained to predict differences between regression targets rather than the targets themselves. A solution to the original regression problem can be…