| FINETUNA: fine-tuning accelerated molecular simulations J Musielewicz, X Wang, T Tian, Z Ulissi Machine Learning: Science and Technology 3 (3), 03LT01, 2022 | 31 | 2022 |
| Substrate-wrapped, single-walled carbon nanotube probes for hydrolytic enzyme characterization NE Kallmyer, J Musielewicz, J Sutter, NF Reuel Analytical chemistry 90 (8), 5209-5216, 2018 | 30 | 2018 |
| Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials Y Hu, J Musielewicz, ZW Ulissi, AJ Medford Machine Learning: Science and Technology 3 (4), 045028, 2022 | 29 | 2022 |
| Influence of sonication conditions and wrapping type on yield and fluorescent quality of noncovalently functionalized single-walled carbon nanotubes NE Kallmyer, T Huynh, JC Graves, J Musielewicz, D Tamiev, NF Reuel Carbon 139, 609-613, 2018 | 12 | 2018 |
| Generalization of graph-based active learning relaxation strategies across materials X Wang, J Musielewicz, R Tran, SK Ethirajan, X Fu, H Mera, JR Kitchin, ... Machine Learning: Science and Technology 5 (2), 025018, 2024 | 5 | 2024 |
| AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification M Shuaibi, Y Hu, X Lei, BM Comer, M Adams, J Paras, RQ Chen, E Musa, ... Journal of Open Source Software 8 (87), 5035, 2023 | 4 | 2023 |
| Improved Uncertainty Estimation of Graph Neural Network Potentials Using Engineered Latent Space Distances J Musielewicz, J Lan, M Uyttendaele, JR Kitchin The Journal of Physical Chemistry C 128 (49), 20799-20810, 2024 | 1 | 2024 |
| Accessing Numerical Energy Hessians with Graph Neural Network Potentials and Their Application in Heterogeneous Catalysis B Wander, J Musielewicz, R Cheula, JR Kitchin arXiv preprint arXiv:2410.01650, 2024 | 1 | 2024 |
| Improving Uncertainty Estimation Based on Latent Space Distance for Graph Neural Network Potentials J Musielewicz, J Kitchin 2024 AIChE Annual Meeting, 2024 | | 2024 |
| Rotationally Invariant Latent Distances for Uncertainty Estimation of Relaxed Energy Predictions by Graph Neural Network Potentials J Musielewicz, J Lan, M Uyttendaele, JR Kitchin arXiv e-prints, arXiv: 2407.10844, 2024 | | 2024 |
| Transfer Learning of Graph Neural Networks As a General Approach to Accelerate Computational Catalysis Modeling T Tian, A Kolluru, J Musielewicz, J Ock, Z Ulissi 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Accelerating on-the-Fly Active Learning of Catalyst Simulations Using Large Scale Pretrained Models J Musielewicz, M Shuaibi, Z Ulissi 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Uncertainty quantification of wind turbine fatigue lifetime predictions through binning Y Hu, J Musielewicz, ZW Ulissi | | |
| Predictive Uncertainty Quantification for Graph Neural Network Driven Relaxed Energy Calculations J Musielewicz, J Lan, M Uyttendaele NeurIPS 2023 AI for Science Workshop, 0 | | |
