19 citations · 21 across the 2 of their papers we have counts for
5 papers
A Differential Geometry Perspective on Orthogonal Recurrent Models
Omri Azencot, N. Benjamin Erichson, Mirela Ben-Chen +1
Recently, orthogonal recurrent neural networks (RNNs) have emerged as state-of-the-art models for learning long-term dependencies. This class of models mitigates the exploding and…
Modes of Homogeneous Gradient Flows
Ido Cohen, Omri Azencot, Pavel Lifshitz +1
Finding latent structures in data is drawing increasing attention in diverse fields such as image and signal processing, fluid dynamics, and machine learning. In this work we exami…
Lipschitz Recurrent Neural Networks
N. Benjamin Erichson, Omri Azencot, Alejandro Queiruga +2
Viewing recurrent neural networks (RNNs) as continuous-time dynamical systems, we propose a recurrent unit that describes the hidden state's evolution with two parts: a well-unders…
Forecasting Sequential Data using Consistent Koopman Autoencoders
Omri Azencot, N. Benjamin Erichson, Vanessa Lin +1
Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based metho…
Shape Analysis via Functional Map Construction and Bases Pursuit
Omri Azencot, Rongjie Lai
We propose a method to simultaneously compute scalar basis functions with an associated functional map for a given pair of triangle meshes. Unlike previous techniques that put emph…