Data-Intensive Scientific Machine Learning and Analysis - preapplication

Sponsor Deadline: 

Apr 23, 2021

Letter of Intent Deadline: 

Apr 23, 2021

Sponsor: 

Energy DOE Office of Advanced Scientific Computing

UI Contact: 

DOE Data-Intensive Scientific Machine Learning and Analysis
DE-FOA-0002493
Pre-Applications due April 23, 2021
PDF to guidelines   https://science.osti.gov/-/media/grants/pdf/foas/2021/SC_FOA_0002493.pdf

The principal focus of this Program Announcement is on AI/ML for scientific inference and data analysis. Several recent Office of Science reports have highlighted the benefits and computational, mathematical, and statistical challenges in dealing with massive, complex, and multi-modal data from simulations, experiments, and observations. Foundational research will be needed for developing reliable and efficient tools for scientific advances. Also, new techniques and approaches will likely be needed to reap scientific benefits from the extreme heterogeneity of scientific computing technologies (e.g., processors, memory and interconnect systems, sensors) that are emerging.  . . .
It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches. Proposed approaches may include innovative research with one or more key characteristics, such as asynchronous computations, mixed-precision arithmetic, compressed sensing, coupling frameworks, graph and network algorithms, randomization, Monte Carlo or Bayesian methods, differentiable or probabilistic programming, or other relevant facets

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