More Like this

1. Blocks-World Cameras

   https://doi.org/10.1109/CVPR46437.2021.01125  

   Lee, Jongho; Gupta, Mohit (June 2021, IEEE)
2. The Geodynamic World Builder

   https://doi.org/10.5281/zenodo.10794862  

   Fraters, Menno (January 2024, Zenodo)

   The Geodynamic World Builder (GWB) is an open source code library intended to set up initial conditions for computational geodynamic models and/or visualize complex 3d teconic setting, in both Cartesian and Spherical geometries. The inputs for the JSON-style parameter file are not mathematical, but rather a structured nested list describing tectonic features, e.g. a continental, an oceanic or a subducting plate. Each of these tectonic features can be assigned a specific temperature profile (e.g. plate model) or composition label (e.g. uniform). For each point in space, the GWB can return the composition and/or temperature. It is written in C++, but can be used in almost any language through its C, Python and Fortran wrappers. Various examples of 2D and 3D subduction settings are presented. 

   more » « less
3. The Mechanical World of Bacteria

   https://doi.org/10.1016/j.cell.2015.05.005  

   Persat, Alexandre; Nadell, Carey D.; Kim, Minyoung Kevin; Ingremeau, Francois; Siryaporn, Albert; Drescher, Knut; Wingreen, Ned S.; Bassler, Bonnie L.; Gitai, Zemer; Stone, Howard A. (May 2015, Cell)
4. The Microscopic World of Diatoms

   https://doi.org/10.2505/4/tst16_083_08_55  

   Sultany, Molly; Bixby, Rebecca (January 2016, The Science Teacher)
5. Open-World Knowledge Graph Completion

   Shi, Baoxu; Weninger, Tim (April 2018, Association for the Advancement of Artificial Intelligence)

   Knowledge Graphs (KGs) have been applied to many tasks including Web search, link prediction, recommendation, natural language processing, and entity linking. However, most KGs are far from complete and are growing at a rapid pace. To address these problems, Knowledge Graph Completion (KGC) has been proposed to improve KGs by filling in its missing connections. Unlike existing methods which hold a closed-world assumption, i.e., where KGs are fixed and new entities cannot be easily added, in the present work we relax this assumption and propose a new open-world KGC task. As a first attempt to solve this task we introduce an open-world KGC model called ConMask. This model learns embeddings of the entity's name and parts of its text-description to connect unseen entities to the KG. To mitigate the presence of noisy text descriptions, ConMask uses a relationship-dependent content masking to extract relevant snippets and then trains a fully convolutional neural network to fuse the extracted snippets with entities in the KG. Experiments on large data sets, both old and new, show that ConMask performs well in the open-world KGC task and even outperforms existing KGC models on the standard closed-world KGC task. 

   more » « less