A practical guide to solving the stochastic Landau-Lifshitz-Gilbert-Slonczewski equation for macrospin dynamics. - Sebastian Ament; Nikhil Rangarajan; Shaloo Rakheja (CoRR, 2016)

An Efficient Relaxed Projection Method for Constrained Non-negative Matrix Factorization with Application to the Phase-Mapping Problem in Materials Science. - Junwen Bai; Sebastian Ament; Guillaume Perez; John M. Gregoire; Carla P. Gomes (CPAIOR, 2018)

Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics. - Sebastian Ament; Michael O'Neil (Stat. Comput., 2018)

Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy. - Sebastian Ament; John M. Gregoire; Carla P. Gomes (CoRR, 2019)

Deep Reasoning Networks: Thinking Fast and Slow. - Di Chen 001; Yiwei Bai; Wenting Zhao 002; Sebastian Ament; John M. Gregoire; Carla P. Gomes (CoRR, 2019)

Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning. - Di Chen 001; Yiwei Bai; Wenting Zhao 002; Sebastian Ament; John M. Gregoire; Carla P. Gomes (ICML, 2020)

Efficient Projection Algorithms onto the Weighted l1 Ball. - Guillaume Perez; Sebastian Ament; Carla P. Gomes; Michel Barlaud (CoRR, 2020)

On the Optimality of Backward Regression: Sparse Recovery and Subset Selection. - Sebastian Ament; Carla P. Gomes (ICASSP, 2021)

Sparse Bayesian Learning via Stepwise Regression. - Sebastian E. Ament; Carla P. Gomes (ICML, 2021)

Autonomous synthesis of metastable materials. - Sebastian Ament; Maximilian Amsler; Duncan R. Sutherland; Ming-Chiang Chang; Dan Guevarra; Aine B. Connolly; John M. Gregoire; Michael O. Thompson; Carla P. Gomes; R. Bruce van Dover (CoRR, 2021)

Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoning. - Di Chen 001; Yiwei Bai; Sebastian Ament; Wenting Zhao 002; Dan Guevarra; Lan Zhou; Bart Selman; R. Bruce van Dover; John M. Gregoire; Carla P. Gomes (CoRR, 2021)

Constrained Machine Learning: The Bagel Framework. - Guillaume Perez; Sebastian Ament; Carla P. Gomes; Arnaud Lallouet (CoRR, 2021)

Automating crystal-structure phase mapping by combining deep learning with constraint reasoning. - Di Chen 001; Yiwei Bai; Sebastian Ament; Wenting Zhao 002; Dan Guevarra; Lan Zhou; Bart Selman; R. Bruce van Dover; John M. Gregoire; Carla P. Gomes (Nat. Mach. Intell., 2021)

The Fast Kernel Transform. - John Paul Ryan; Sebastian E. Ament; Carla P. Gomes; Anil Damle (AISTATS, 2022)

Generalized Matching Pursuits for the Sparse Optimization of Separable Objectives. - Sebastian Ament; Carla P. Gomes (ICASSP, 2022)

Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation. - Sebastian E. Ament; Carla P. Gomes (ICML, 2022)

Efficient projection algorithms onto the weighted ℓ1 ball. - Guillaume Perez; Sebastian Ament; Carla P. Gomes; Michel Barlaud (Artif. Intell., 2022)

Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. - Aryan Deshwal; Sebastian Ament; Maximilian Balandat; Eytan Bakshy; Janardhan Rao Doppa; David Eriksson (AISTATS, 2023)

Unexpected Improvements to Expected Improvement for Bayesian Optimization. - Sebastian Ament; Samuel Daulton; David Eriksson; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2023)

Probabilistic Phase Labeling and Lattice Refinement for Autonomous Material Research. - Ming-Chiang Chang; Sebastian Ament; Maximilian Amsler; Duncan R. Sutherland; Lan Zhou; John M. Gregoire; Carla P. Gomes; R. Bruce van Dover; Michael O. Thompson (CoRR, 2023)

Sustainable Concrete via Bayesian Optimization. - Sebastian Ament; Andrew Witte; Nishant Garg; Julius Kusuma (CoRR, 2023)

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers. - P. Rodriguez-Fernandez; N. T. Howard; A. Saltzman; S. Kantamneni; J. Candy; C. Holland; Maximilian Balandat; Sebastian Ament; A. E. White (CoRR, 2023)

Robust Gaussian Processes via Relevance Pursuit. - Sebastian Ament; Elizabeth Santorella; David Eriksson; Ben Letham; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2024)

Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure. - Jihao Andreas Lin; Sebastian Ament; Maximilian Balandat; Eytan Bakshy (CoRR, 2024)

Scalable Gaussian Processes with Latent Kronecker Structure. - Jihao Andreas Lin; Sebastian Ament; Maximilian Balandat; David Eriksson; José Miguel Hernández-Lobato; Eytan Bakshy (CoRR, 2025)