activity
20192022
most citedNeural Manifold Clustering and Embedding

13 citations · 15 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20222 cited

Unsupervised Learning of Structured Representations via Closed-Loop Transcription

Shengbang Tong, Xili Dai, Yubei Chen +5

This paper proposes an unsupervised method for learning a unified representation that serves both discriminative and generative purposes. While most existing unsupervised learning…

cs.LG202213 cited

Neural Manifold Clustering and Embedding

Zengyi Li, Yubei Chen, Yann LeCun +1

Given a union of non-linear manifolds, non-linear subspace clustering or manifold clustering aims to cluster data points based on manifold structures and also learn to parameterize…

stat.ML2020

A Neural Network MCMC sampler that maximizes Proposal Entropy

Zengyi Li, Yubei Chen, Friedrich T. Sommer

Markov Chain Monte Carlo (MCMC) methods sample from unnormalized probability distributions and offer guarantees of exact sampling. However, in the continuous case, unfavorable geom…

stat.ML2020

Complex Amplitude-Phase Boltzmann Machines

Zengyi Li, Friedrich T. Sommer

We extend the framework of Boltzmann machines to a network of complex-valued neurons with variable amplitudes, referred to as Complex Amplitude-Phase Boltzmann machine (CAP-BM). Th…

stat.ML2019

Learning Energy-Based Models in High-Dimensional Spaces with Multi-scale Denoising Score Matching

Zengyi Li, Yubei Chen, Friedrich T. Sommer

Energy-Based Models (EBMs) assign unnormalized log-probability to data samples. This functionality has a variety of applications, such as sample synthesis, data denoising, sample r…