ScholarBERT: Bigger is Not Always Better

AIEADA 1.0: Efficient high-dimensional variational data assimilation with machine-learned reduced-order models

An Investigation of Multiple Classifications of Clouds Over Mid-latitude Cyclones

Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl

Autonomous Synthesis and Inverse Design of Electronic Polymers with High Efficiency and Accuracy

Cartesian Equivariant Representations for Learning and Understanding Molecular Orbitals

Cartesian Equivariant Representations for Learning and Understanding Molecular Orbitals

Deep Learning for Molecular Orbitals

ESGF Next Generation and preparations for CMIP7

E_min: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability

Fast and accurate learned multiresolution dynamical downscaling for precipitation

GHP-MOFassemble: Diffusion modeling, high throughput screening, and molecular dynamics for rational discovery of novel metal-organic frameworks for carbon capture at scale

Making Common Fund data more findable: Catalyzing a Data Ecosystem

Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group (Preprint)

Performance, Resilience, and Security in Moving Data from the Fog to the Cloud: The DYNAMO Transfer Framework Approach

Real-time porosity mapping and visualization for synchrotron tomography

Real-time porosity mapping and visualization for synchrotron tomography

StormSeeker: A Machine-Learning-Based Mediterranean Storm Tracer

The Delta Variant Had Negligible Impact on COVID-19 Vaccine Effectiveness in the USA

The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0)

The Modern Research Data Portal: A design pattern for networked, data-intensive science

The Modern Research Data Portal: A design pattern for networked, data-intensive science

Towards High Performance Data Analytics for Climate Change

Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE Materials DB): An Open-Access Resource for Ground and Excited State Properties of Organic Molecules

Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE Materials DB): An Open-Access Resource for Ground and Excited State Properties of Organic Molecules

Will It Blend? Mixing Numerical and Machine-Learned Physics Quantities for Accurate on-the-Fly Surrogate Modeling