Model re-parameterization is the practice of merging multiple computational models at the inference stage to accelerate inference time. In YOLOv7, the technique“Extended efficient layer aggregation networks”or E-ELAN is used to perform this feat. E-ELANimplements expand, shuffle, and merge cardinal...
Recently, a system-level model reduction technique for flexible multibody systems, Global Modal Parameterization (GMP), has been proposed. This method is based on an interpolation of ROMs for different undeformed configurations in order to reduce model equation assembly time. As is shown in this ...
Our results suggest that LULC effects need to be better incorporated into the conceptualization and parameterization of infiltration and percolation in hydrologic models to obtain realistic predictions concerning water quality and quantity.doi:10.2136/vzj2009.0089S. Bachmair...
Args: ... aparam: Atomic parameters tensor of shape [natoms, numb_aparam] ... """ Line range hint 21-38: Consider documenting the multi-backend testing strategy. While this PR focuses on adding use_aparam_as_mask support for the pt backend, these changes to the TF test utilities sug...
The overparameterization of LLMs presents a significant challenge: they tend to memorize extensive amounts of training data. This becomes particularly problematic in RAG scenarios when the context conflicts with this "implicit" knowledge. However, the situation escalates further when...
The initial and boundary conditions of meteorological parameters were generated from the National Center for Environmental Prediction (NCEP) Final Analysis (FNL) data, with a horizontal resolution of 1° × 1° and a temporal resolution of 6 h. Table 1. Physics parameterization options used in ...
The Decision Support System for Agricultural Technology Transfer (DSSAT) was used to quantify the impact of climate change on maize yield and the potential benefits of the use of drought-tolerant maize variety over non-drought tolerant variety in savanna
Our results indicated that under a unified parameterization scheme, EC-LUE and VPM yielded the best performance in simulating GPP variations, followed by GLO-PEM, CASA, and C-fix, while MODIS also demonstrated reliable GPP estimation ability. The results of the model fusion across different forest...
Citation: Ahumada, L.; Carreño, E.; Anglès, A.; Dujovne, D.; Palacios Játiva, P. Behind the Door: Practical Parameterization of Propagation Parameters for IEEE 802.11ad Use Cases. Technologies 2024, 12, 85. https://doi.org/10.3390/ technologies12060085 Academic Editor: Sotirios K. Gou...
Note: When you use next(), Python calls .__next__() on the function you pass in as a parameter. There are some special effects that this parameterization allows, but it goes beyond the scope of this article. Experiment with changing the parameter you pass to next() and see what happen...