114 citations · 124 across the 7 of their papers we have counts for
7 papers
Anomaly Detection with Variance Stabilized Density Estimation
Amit Rozner, Barak Battash, Henry Li +2
We propose a modified density estimation problem that is highly effective for detecting anomalies in tabular data. Our approach assumes that the density function is relatively stab…
Autoregressive Generative Modeling with Noise Conditional Maximum Likelihood Estimation
Henry Li, Yuval Kluger
We introduce a simple modification to the standard maximum likelihood estimation (MLE) framework. Rather than maximizing a single unconditional likelihood of the data under the mod…
Neural Inverse Transform Sampler
Henry Li, Yuval Kluger
Any explicit functional representation of a density is hampered by two main obstacles when we wish to use it as a generative model: designing so that sampling is fast, and…
Support Recovery with Stochastic Gates: Theory and Application for Linear Models
Soham Jana, Henry Li, Yutaro Yamada +1
Consider the problem of simultaneous estimation and support recovery of the coefficient vector in a linear data model with additive Gaussian noise. We study the problem of estimati…
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging
Hannah Lawrence, David A. Barmherzig, Henry Li +2
Phase retrieval is the inverse problem of recovering a signal from magnitude-only Fourier measurements, and underlies numerous imaging modalities, such as Coherent Diffraction Imag…
Variational Diffusion Autoencoders with Random Walk Sampling
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng +1
Variational autoencoders (VAEs) and generative adversarial networks (GANs) enjoy an intuitive connection to manifold learning: in training the decoder/generator is optimized to app…
SpectralNet: Spectral Clustering using Deep Neural Networks
Uri Shaham, Kelly Stanton, Henry Li +3
Spectral clustering is a leading and popular technique in unsupervised data analysis. Two of its major limitations are scalability and generalization of the spectral embedding (i.e…