1 code implementation • Human Brain Mapping 2021 • Svanera, M., Benini, S., Bontempi, D., Muckli, L
An essential step in many functional and structural neuroimaging studies is segmentation, the operation of partitioning the MR images in anatomical structures.
no code implementations • 12 Nov 2020 • Botelho, Joshi, A., Khara, Sarkar, S., Hegde, C., Rao, V., Adavani, S.S., & Ganapathysubramanian, B.
Here we report on a software framework for data parallel distributed deep learning that resolves the twin challenges of training these large SciML models training in reasonable time as well as distributing the storage requirements.
1 code implementation • Computer Physics Communications 2019 • Chmiela, S., Sauceda, H. E., Poltavsky, I., Müller, K.-R., Tkatchenko, A.
We present an optimized implementation of the recently proposed symmetric gradient domain machine learning (sGDML) model.
1 code implementation • Nature Communications 2018 • Chmiela, S., Sauceda, H. E., Müller, K.-R., Tkatchenko, A.
We present MD simulations, for flexible molecules with up to a few dozen atoms and provide insights into the dynamical behavior of these molecules.
1 code implementation • Science Advances 2017 • Chmiela, S., Tkatchenko, A., Sauceda, H. E., Poltavsky, I., Schütt, K. T., Müller, K.-R.
Using conservation of energy—a fundamental property of closed classical and quantum mechanical systems—we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories.
no code implementations • 14 May 2014 • McDuff, D., Gontarek, S., and Picard, R
Remote measurement of the blood volume pulse via photoplethysmography (PPG) using digital cameras and ambient light has great potential for healthcare and affective computing.