LossPlot: A Better Way to Visualize Loss Landscapes
Robert Bain, Mikhail Tokarev, Harsh Kothari, Rahul Damineni

TL;DR
LossPlot is a user-friendly platform that simplifies the visualization of deep neural network loss landscapes, enabling synchronized manipulation of multiple minimizers and offering customizable visualization features.
Contribution
This work introduces LossPlot, a semi-automated, interactive tool for visualizing loss landscapes with features not available in existing methods.
Findings
Enhanced visualization of loss landscapes with synchronized minimizer manipulation
User-friendly interface with customizable visualization options
Facilitates deeper understanding of neural network training dynamics
Abstract
Investigations into the loss landscapes of deep neural networks are often laborious. This work documents our user-driven approach to create a platform for semi-automating this process. LossPlot accepts data in the form of a csv, and allows multiple trained minimizers of the loss function to be manipulated in sync. Other features include a simple yet intuitive checkbox UI, summary statistics, and the ability to control clipping which other methods do not offer.
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Taxonomy
TopicsAdvanced Neural Network Applications · Neural Networks and Applications · Adversarial Robustness in Machine Learning
