Results 71 to 80 of about 67,464 (283)
CSGNet: Neural Shape Parser for Constructive Solid Geometry
, 2018 We present a neural architecture that takes as input a 2D or 3D shape and outputs a program that generates the shape. The instructions in our program are based on constructive solid geometry principles, i.e., a set of boolean operations on shape ...
Goyal, Rishabh +4 more
core +1 more source
Diagnosing coastal processes using machine learning and ocean buoyancy gliders
Limnology and Oceanography, EarlyView.Abstract Ocean buoyancy gliders provide a comprehensive view of the water column, offering more than simply a snapshot of a single moment in time or space. In this study, we applied the established machine learning method, k‐means clustering, to a glider dataset collected in the summer of 2015 in the northern Gulf of Mexico.
Robert L. Iles IV +3 more
wiley +1 more source
A hybrid top-down, bottom-up approach for 3D space parsing using dense RGB point clouds [PDF]
, 2023 M. Mehranfar +2 more
openalex +1 more source
Limnology and Oceanography, EarlyView.Abstract Suspended particulate matter, or seston, represents an understudied flux of carbon (C), nitrogen (N), and phosphorus (P) in river networks. Here, we summarize riverine seston C : N : P stoichiometry data from 27 streams and rivers sampled regularly from 2014 to 2022 across the United States by the National Ecological Observatory Network (NEON).
David W. P. Manning +3 more
wiley +1 more source
GseaVis: An R Package for Enhanced Visualization of Gene Set Enrichment Analysis in Biomedicine
Med Research, EarlyView.ABSTRACT Gene set enrichment analysis (GSEA) is a widely used computational method for determining whether predefined sets of genes show statistically significant concordant differences between two biological states. Despite its popularity, effective visualization of GSEA results remains challenging particularly for users seeking to extract meaningful ...
Jun Zhang +3 more
wiley +1 more source
A Survey of Unsupervised Dependency Parsing [PDF]
arXiv, 2020 Syntactic dependency parsing is an important task in natural language processing. Unsupervised dependency parsing aims to learn a dependency parser from sentences that have no annotation of their correct parse trees. Despite its difficulty, unsupervised parsing is an interesting research direction because of its capability of utilizing almost unlimited
arxiv
Optimal LZ-End Parsing is Hard [PDF]
arXiv, 2023 LZ-End is a variant of the well-known Lempel-Ziv parsing family such that each phrase of the parsing has a previous occurrence, with the additional constraint that the previous occurrence must end at the end of a previous phrase. LZ-End was initially proposed as a greedy parsing, where each phrase is determined greedily from left to right, as the ...
arxiv
Movement Disorders, EarlyView.Abstract Background Individual variability in clinical response to dopamine replacement therapy (DRT) is a key barrier to efficacious treatment for patients with Parkinson's disease (PD). A better understanding of the neurobiological sources of such interindividual differences is necessary to personalize DRT prescribing, inform future clinical ...
Alex I. Wiesman +5 more
wiley +1 more source
Journal of Industrial Ecology, Volume 26, Issue 6, Page 1871-1881, December 2022., 2022 Abstract Ships, sailing in favorable wind or obstructed by wind, will operate with different output power of the engines, and the exhaust emissions will be different even though the ships are sailing at the same ground speed. In this study, the influence of wind was taken into consideration; the ship emission inventory (0.025° × 0.025°) in China of a ...
Xinyi Fu +4 more
wiley +1 more source
Predicting Research Trends From Arxiv [PDF]
arXiv, 2019 We perform trend detection on two datasets of Arxiv papers, derived from its machine learning (cs.LG) and natural language processing (cs.CL) categories. Our approach is bottom-up: we first rank papers by their normalized citation counts, then group top-ranked papers into different categories based on the tasks that they pursue and the methods they use.
arxiv