LLNL
Lab Offers Forum On Machine Learning For Industry
Lawrence Livermore National Laboratory (LLNL) is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10. Pre-registrations are open for the forum, which aims to foster and illustrate the adoption of machine learning methods for practical industrial …
Novel Deep Learning Framework For Symbolic Regression
Lawrence Livermore National Laboratory (LLNL) computer scientists have developed a new framework and an accompanying visualization tool that leverages deep reinforcement learning for symbolic regression problems, outperforming baseline methods on benchmark problems. The paper was recently accepted as an oral presentation at the International Conference on Learning Representations (ICLR 2021), one of the top machine …
‘Self-trained’ Deep Learning To Improve Disease Diagnosis
New work by computer scientists at Lawrence Livermore National Laboratory (LLNL) and IBM Research on deep learning models to accurately diagnose diseases from X-ray images with less labeled data won the Best Paper award for Computer-Aided Diagnosis at the SPIE Medical Imaging Conference on Feb. 19. The technique, which includes novel regularization and “self-training” strategies, …
Lab Launches Interdisciplinary Space Science Institute
What are the next world-class, game-changing concepts and technologies that will address the most important questions in astrophysics or planetary science? Lawrence Livermore National Laboratory (LLNL) researchers will soon be better equipped to answer this question with the launch this month of a new Space Science Institute (SSI), intended to boost cross-discipline collaboration and discovery. …
Lab Researchers Explore ‘Learn-By-Calibration’ Approach To Deep Learning To Accurately Emulate Scientific Process
Lawrence Livermore National Laboratory (LLNL) computer scientists have developed a new deep learning approach to designing emulators for scientific processes that is more accurate and efficient than existing methods. In a paper published by Nature Communications, an LLNL team describes a “Learn-by-Calibrating” (LbC) method for creating powerful scientific emulators that could be used as proxies …
Lab Will Co-Lead NASA Mission To Study Stars, Planets
NASA has selected Lawrence Livermore National Laboratory (LLNL) and Goddard Space Flight Center (GSFC) to serve as lead institutions for the Pandora scientific mission that will study 20 stars and their 39 exoplanets. The goal of the Pandora mission is to learn about starspots (akin to sunspots) and identify which of these exoplanets are …
LLNL Develops Optical Capability For Thin-film Neural Implants To Look Into Brain Activity
Combining hybrid polymer materials with microfabrication and 3D printing, Lawrence Livermore National Laboratory (LLNL) has developed an ultra-compact, lightweight and minimally invasive optoelectronic neural implant that could be used for long-term studies of brain activity. The new implantable devices are built upon a new platform LLNL researchers are calling POEMS (Polymeric Opto-Electro-Mechanical Systems) and represent …
Girls Who Code – ‘Big’ Program Goes Virtual
Livermore High School freshman Amber Belk is focused on studying chemical engineering in college, but through the Girls Who Code – “Big” program, she gained a new appreciation for how high performance computers that can model the types of molecules she will be studying. “Writing software codes and using the Linux operating system was really …
LLNL, Partners Open Access To CO2 Storage Simulator
After more than two years of joint research, Lawrence Livermore National Laboratory (LLNL), Total and Stanford University are releasing an open-source, high-performance simulator for large-scale geological carbon dioxide (CO2) storage. The GEOSX simulator will enable researchers around the world to build on the work of the three partners, providing an open framework to accelerate the development of carbon capture, utilization …
LLNL To Provide Supercomputing Resources To Universities Selected By NNSA Advanced Simulation And Computing Program
Lawrence Livermore National Laboratory (LLNL) will provide significant computing resources to students and faculty from nine universities that were newly selected for participation in the National Nuclear Security Administration (NNSA)’s Predictive Science Academic Alliance Program (PSAAP). The program is funded by NNSA’s Office of Advanced Simulation and Computing (ASC) program. The NNSA on Thursday announced recipients of funding and five-year cooperative agreements …