all AI news
Amortized Inference for Heterogeneous Reconstruction in Cryo-EM. (arXiv:2210.07387v1 [cs.CV])
Oct. 17, 2022, 1:11 a.m. | Axel Levy, Gordon Wetzstein, Julien Martel, Frederic Poitevin, Ellen D. Zhong
cs.LG updates on arXiv.org arxiv.org
Cryo-electron microscopy (cryo-EM) is an imaging modality that provides
unique insights into the dynamics of proteins and other building blocks of
life. The algorithmic challenge of jointly estimating the poses, 3D structure,
and conformational heterogeneity of a biomolecule from millions of noisy and
randomly oriented 2D projections in a computationally efficient manner,
however, remains unsolved. Our method, cryoFIRE, performs ab initio
heterogeneous reconstruction with unknown poses in an amortized framework,
thereby avoiding the computationally expensive step of pose search while …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Principal Machine Learning Engineer (AI, NLP, LLM, Generative AI)
@ Palo Alto Networks | Santa Clara, CA, United States
Consultant Senior Data Engineer F/H
@ Devoteam | Nantes, France