HydroGraphNet boosts watershed predictions of daily flow and nitrogen in sparse data regions

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...
EurekAlert!

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...
Scripps Institution of Oceanography

New AI Approach Reveals Ocean Currents in Unprecedented Detail

Scientists have developed a new method to measure ocean surface currents over large areas in greater detail than ever before.
Scientific Research Publishing

Rossi, E., et al. (2020) Temporal Graph Networks for Deep Learning on Dynamic Graphs. arXiv: 2006.10637.

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Scientific Research Publishing

Kipf, T. and Welling, M. (2016) Semi-Supervised Classification with Graph Convolutional Networks. arXiv: 1609.02907.

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
ahajournals.org

Abstract TAC238: Predicting Peptide-Human Leukocyte Antigen and Isolevuglandin Immunogenicity in Hypertension Using Structure-based Deep Learning

Introduction: Isolevuglandin (IsoLG)-adducted peptides contribute to hypertension by enhancing class I human leukocyte antigen (HLA)-mediated T cell activation. The capacity of different HLA alleles ...
PNAS

A protein dynamics–based deep learning model enhances predictions of fitness and epistasis

Predicting the effects of multiple mutations on protein function is challenging due to the intricate interplay between residues. Machine learning has advanced these efforts, but traditional neural ...
IEEE

A Graph-based Deep Reinforcement Learning Model for Task Scheduling on Heterogeneous Resource-Elastic Management of Resource Pool

Abstract: As cloud computing revolutionizes various fields, the demand for scalable and flexible computing resources has grown significantly. Applications in large-scale engineering simulations, ...
IEEE

Graph-Based Dual-Agent Deep Reinforcement Learning for Dynamic Human–Machine Hybrid Reconfiguration Manufacturing Scheduling

Abstract: Human–machine hybrid reconfiguration manufacturing is an emerging paradigm in the field of precision equipment production and can greatly improve the production capability of the workshop.
Sports Illustrated

Takeaways From BC Football's First Two Deep Depth Chart: Likes, Surprises, Concerns

On Tuesday afternoon, Boston College football released its first two-deep depth chart ahead of the program’s season-opening contest at home against Fordham on Saturday at 2 p.m. There are plenty of ...