Search Results for author:
Found 2 papers, 0 papers with code
Finite-time Lyapunov exponents of deep neural networks
We compute how small input perturbations affect the output of deep neural networks, exploring an analogy between deep networks and dynamical systems, where the growth or decay of local perturbations is characterised by finite-time Lyapunov exponents.
Looking at the posterior: accuracy and uncertainty of neural-network predictions
Here we show that prediction accuracy depends on both epistemic and aleatoric uncertainty in an intricate fashion that cannot be understood in terms of marginalized uncertainty distributions alone.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
