12 citations · 25 across the 7 of their papers we have counts for
3 papers · 1 filter
Differentiable Implicit Layers
Andreas Look, Simona Doneva, Melih Kandemir +2
In this paper, we introduce an efficient backpropagation scheme for non-constrained implicit functions. These functions are parametrized by a set of learnable weights and may optio…
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
Manuel Haussmann, Sebastian Gerwinn, Andreas Look +2
Neural Stochastic Differential Equations model a dynamical environment with neural nets assigned to their drift and diffusion terms. The high expressive power of their nonlinearity…
A Deterministic Approximation to Neural SDEs
Andreas Look, Melih Kandemir, Barbara Rakitsch +1
Neural Stochastic Differential Equations (NSDEs) model the drift and diffusion functions of a stochastic process as neural networks. While NSDEs are known to make accurate predicti…