Visualizing Loss Landscapes of Neural Networks [P]

Hey r/MachineLearning, Visualizing the loss landscape of a neural network is notoriously tricky since we can't naturally comprehend million-dimensional spaces. We often rely on basic 2D contour analogies, which don't always capture the true geometry of the space or the sharpness of local minima. I built an interactive browser experiment to help build better intuitions for this. It maps how different optimizers navigate these spaces and lets you actually visualize the terrain. To generate the 3D surface plots, I used the methodology from Li (NeurIPS 2018.