Jun 10, 2019 · This observation motivated the introduction of so-called Neural ODEs, which allow more general discretization schemes with adaptive time ...

This observation motivated the introduction of so-called Neural ODEs, in which other discretization schemes and/or adaptive time stepping techniques can be used ...

We provide a general framework that extends Neural ODEs to system of coupled ODEs which allows coupled evolution of both model parameters and activations. This ...

Jun 10, 2019 · Here, we propose ANODEV2, which is an extension of the approach that also allows evolution of the neural network parameters, in a coupled ODE- ...

ANODEV2 allows the evolution of both weights and activations by a coupled ... a coupled ODE based framework, motivated by the works in neural evolution.

Aug 3, 2021 · ANODEV2: A Coupled Neural ODE Evolution Framework. It has been observed that residual networks can be viewed as the explicit Euler ...

This observation motivated the introduction of so-called Neural ODEs, which allow more general discretization schemes with adaptive time stepping. Here, we ...

ANODE is a neural ODE framework based on this paper. It provides unconditionally accurate gradients for Neural ODEs, using adjoint method.

... framework that allows ODE-based evolution for both the weights and the activations, in a coupled formulation. Such an approach provides more modeling ...

A recent solution was proposed by Chen et al. to reverse ODE solve and avoid storing z(t). • Reduces memory cost from O(LNt) -> O(L).