Differentiable Implicit Layers

• URL: http://arxiv.org/abs/2010.07078v2
• Date: Mon, 16 Nov 2020 10:25:13 GMT
• Title: Differentiable Implicit Layers
• Authors: Andreas Look, Simona Doneva, Melih Kandemir, Rainer Gemulla, Jan Peters
• Abstract summary: In this paper, we introduce an efficient backpropagation scheme for non-constrained implicit functions. We demonstrate our scheme on different applications: (i) neural ODEs with the implicit Euler method, and (ii) system identification in model predictive control.
• Score: 37.14578406197477
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 optionally depend on some input; making them perfectly suitable as a learnable layer in a neural network. We demonstrate our scheme on different applications: (i) neural ODEs with the implicit Euler method, and (ii) system identification in model predictive control.

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