118 citations · 440 across the 31 of their papers we have counts for
11 papers · 1 filter
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
N. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney
In this paper, we present a novel approach to modeling long-term dependencies in sequential data by introducing a gated recurrent unit (GRU) with a weighted time-delay feedback mec…
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
Liam Hodgkinson, Chris van der Heide, Fred Roosta +1
Despite their importance for assessing reliability of predictions, uncertainty quantification (UQ) measures for machine learning models have only recently begun to be rigorously ch…
Gradient Gating for Deep Multi-Rate Learning on Graphs
T. Konstantin Rusch, Benjamin P. Chamberlain, Michael W. Mahoney +2
We present Gradient Gating (G), a novel framework for improving the performance of Graph Neural Networks (GNNs). Our framework is based on gating the output of GNN layers with…
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney +1
Physics-informed neural networks (PINNs) incorporate physical knowledge from the problem domain as a soft constraint on the loss function, but recent work has shown that this can l…
Learning differentiable solvers for systems with hard constraints
Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan
We introduce a practical method to enforce partial differential equation (PDE) constraints for functions defined by neural networks (NNs), with a high degree of accuracy and up to…
Neurotoxin: Durable Backdoors in Federated Learning
Zhengming Zhang, Ashwinee Panda, Linyue Song +5
Due to their decentralized nature, federated learning (FL) systems have an inherent vulnerability during their training to adversarial backdoor attacks. In this type of attack, the…