15 citations · 50 across the 8 of their papers we have counts for
4 papers · 1 filter
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Ronen Basri, David Jacobs, Yoni Kasten +1
We study the relationship between the frequency of a function and the speed at which a neural network learns it. We build on recent results that show that the dynamics of overparam…
Adversarially robust transfer learning
Ali Shafahi, Parsa Saadatpanah, Chen Zhu +4
Transfer learning, in which a network is trained on one task and re-purposed on another, is often used to produce neural network classifiers when data is scarce or full-scale train…
Understanding the (un)interpretability of natural image distributions using generative models
Ryen Krusinga, Sohil Shah, Matthias Zwicker +2
Probability density estimation is a classical and well studied problem, but standard density estimation methods have historically lacked the power to model complex and high-dimensi…
Neural Inverse Rendering of an Indoor Scene from a Single Image
Soumyadip Sengupta, Jinwei Gu, Kihwan Kim +3
Inverse rendering aims to estimate physical attributes of a scene, e.g., reflectance, geometry, and lighting, from image(s). Inverse rendering has been studied primarily for single…