Sebastian Ament
Hesco (United States)(US)
Publications by Year
Research Areas
Machine Learning in Materials Science, Gaussian Processes and Bayesian Inference, Catalysis and Oxidation Reactions, Sparse and Compressive Sensing Techniques, Advanced Multi-Objective Optimization Algorithms
Most-Cited Works
- → Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams(2021)76 cited
- → Automating crystal-structure phase mapping by combining deep learning with constraint reasoning(2021)62 cited
- → Unexpected Improvements to Expected Improvement for Bayesian Optimization(2023)43 cited
- → CRYSTAL: a multi-agent AI system for automated mapping of materials’ crystal structures(2019)34 cited
- → Multi-component background learning automates signal detection for spectroscopic data(2019)32 cited
- → Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers(2024)30 cited
- → Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics(2017)19 cited
- Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning(2020)
- → Deep Reasoning Networks: Thinking Fast and Slow(2019)11 cited
- → Solving the stochastic Landau-Lifshitz-Gilbert-Slonczewski equation for monodomain nanomagnets : A survey and analysis of numerical techniques(2016)11 cited