13 citations · 13 across the 3 of their papers we have counts for
4 papers
Near-Universal Multiplicative Updates for Nonnegative Einsum Factorization
John Hood, Aaron Schein
Despite the ubiquity of multiway data across scientific domains, there are few performant and user-friendly methods that fit non-standard nonnegative tensor factorization models ta…
Broad Spectrum Structure Discovery in Large-Scale Higher-Order Networks
John Hood, Caterina De Bacco, Aaron Schein
Complex systems are often driven by higher-order interactions among multiple units, naturally represented as hypergraphs. Understanding dependency structures within these hypergrap…
The ALCORE Tensor Decomposition for Sparse Count Data
John Hood, Aaron Schein
This paper introduces ALCORE, a new form of probabilistic non-negative tensor decomposition. ALCORE is a Tucker decomposition where the number of non-zero elements…
Model-assisted deep learning of rare extreme events from partial observations
Anna Asch, Ethan Brady, Hugo Gallardo +3
To predict rare extreme events using deep neural networks, one encounters the so-called small data problem because even long-term observations often contain few extreme events. Her…