29 citations · 88 across the 10 of their papers we have counts for
14 papers
Multi-modal Differentiable Unsupervised Feature Selection
Junchen Yang, Ofir Lindenbaum, Yuval Kluger +1
Multi-modal high throughput biological data presents a great scientific opportunity and a significant computational challenge. In multi-modal measurements, every sample is observed…
DiSC: Differential Spectral Clustering of Features
Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe
Selecting subsets of features that differentiate between two conditions is a key task in a broad range of scientific domains. In many applications, the features of interest form cl…
Weakly Supervised Indoor Localization via Manifold Matching
Erez Peterfreund, Ioannis G. Kevrekidis, Ariel Jaffe
Inferring the location of a mobile device in an indoor setting is an open problem of utmost significance. A leading approach that does not require the deployment of expensive infra…
Spectral Top-Down Recovery of Latent Tree Models
Yariv Aizenbud, Ariel Jaffe, Meng Wang +5
Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying…
Super-resolution multi-reference alignment
Tamir Bendory, Ariel Jaffe, William Leeb +2
We study super-resolution multi-reference alignment, the problem of estimating a signal from many circularly shifted, down-sampled, and noisy observations. We focus on the low SNR…
Spectral neighbor joining for reconstruction of latent tree models
Ariel Jaffe, Noah Amsel, Yariv Aizenbud +3
A common assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model. An important example is phylogene…