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Found 5 papers, 3 papers with code
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
While we can control the computational cost by choosing the number of layers in standard architectures, in NDEs the number of neural network evaluations for a forward pass can depend on the number of steps of the adaptive ODE solver.
AutoMat: Accelerated Computational Electrochemical systems Discovery
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation.
Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks
Modern design, control, and optimization often requires simulation of highly nonlinear models, leading to prohibitive computational costs.
Circuitscape in Julia: High Performance Connectivity Modelling to Support Conservation Decisions
Connectivity across landscapes influences a wide range of conservation-relevant ecological processes, including species movements, gene flow, and the spread of wildfire, pests, and diseases.
Fashionable Modelling with Flux
Machine learning as a discipline has seen an incredible surge of interest in recent years due in large part to a perfect storm of new theory, superior tooling, renewed interest in its capabilities.
