88 citations · 139 across the 10 of their papers we have counts for
10 papers
pmwd: A Differentiable Cosmological Particle-Mesh -body Library
Yin Li, Libin Lu, Chirag Modi +7
The formation of the large-scale structure, the evolution and distribution of galaxies, quasars, and dark matter on cosmological scales, requires numerical simulations. Differentia…
Vitruvion: A Generative Model of Parametric CAD Sketches
Ari Seff, Wenda Zhou, Nick Richardson +1
Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key…
Compressed sensing in the presence of speckle noise
Wenda Zhou, Shirin Jalali, Arian Maleki
The problem of recovering a structured signal from its linear measurements in the presence of speckle noise is studied. This problem appears in many imaging systems such as synthet…
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
We study the problem of out-of-sample risk estimation in the high dimensional regime where both the sample size and number of features are large, and can be less than…
Discrete Object Generation with Reversible Inductive Construction
Ari Seff, Wenda Zhou, Farhan Damani +2
The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs. However, constructio…
Denoising of structured random processes
Wenda Zhou, Shirin Jalali
Denoising stationary process corrupted by additive white Gaussian noise is a classic and fundamental problem in information theory and statistical signal processi…
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Shuaiwen Wang, Wenda Zhou, Arian Maleki +2
Consider the following class of learning schemes: \begin{equation} \label{eq:main-problem1} \hat{\boldsymbolβ} := \underset{\boldsymbolβ \in \mathcal{C}}{\arg\min} \;\sum_{j=1}^n \…
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang, Wenda Zhou, Haihao Lu +2
Consider the following class of learning schemes: $$\hat{\boldsymbolβ} := \arg\min_{\boldsymbolβ}\;\sum_{j=1}^n \ell(\boldsymbol{x}_j^\top\boldsymbolβ; y_j) + λR(\boldsymbolβ),\qqu…
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Victor Veitch, Morgane Austern, Wenda Zhou +2
Empirical risk minimization is the main tool for prediction problems, but its extension to relational data remains unsolved. We solve this problem using recent ideas from graph sam…
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach
Wenda Zhou, Victor Veitch, Morgane Austern +2
Modern neural networks are highly overparameterized, with capacity to substantially overfit to training data. Nevertheless, these networks often generalize well in practice. It has…