22 citations · 22 across the 6 of their papers we have counts for
6 papers
W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling
Hossein Babaei, Mel White, Richard G. Baraniuk
State Space Models (SSMs) have emerged as powerful components for sequence modeling, enabling efficient handling of long-range dependencies via linear recurrence and convolutional…
WaLRUS: Wavelets for Long-range Representation Using SSMs
Hossein Babaei, Mel White, Sina Alemohammad +1
State-Space Models (SSMs) have proven to be powerful tools for modeling long-range dependencies in sequential data. While the recent method known as HiPPO has demonstrated strong p…
SaFARi: State-Space Models for Frame-Agnostic Representation
Hossein Babaei, Mel White, Sina Alemohammad +1
State-Space Models (SSMs) have re-emerged as a powerful tool for online function approximation, and as the backbone of machine learning models for long-range dependent data. Howeve…
Self-Consuming Generative Models Go MAD
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi +5
Seismic advances in generative AI algorithms for imagery, text, and other data types has led to the temptation to use synthetic data to train next-generation models. Repeating this…
TITAN: Bringing The Deep Image Prior to Implicit Representations
Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi +6
We study the interpolation capabilities of implicit neural representations (INRs) of images. In principle, INRs promise a number of advantages, such as continuous derivatives and a…
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels
Sina Alemohammad, Hossein Babaei, Randall Balestriero +8
High dimensionality poses many challenges to the use of data, from visualization and interpretation, to prediction and storage for historical preservation. Techniques abound to red…