This edge correction method is only appropriate for square or rectangular shaped study areas. String Study Area Method (Optional) Specifies the region to use for the study area. The K Function is sensitive to changes in study area size so careful selection of this value is impor...
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square(doc_y), 1, True)) prod = tf.reduce_sum(tf.multiply(tf.tile(query_y, [NEG + 1, 1]), doc_y), 1, True) norm_prod = tf.multiply(query_norm, doc_norm) # cos_sim_raw = query * doc / (||query|| * ||doc||) cos_sim_raw = tf.truediv(prod, norm_prod) # gamma...
The observation of an agent is partially observable and consists of a 3x3 (configurable) square centred on the agent. Inside this limited grid, all entities are observable: The location, the rotation and whether the agent is carrying a shelf. The location and rotation of other robots. Shelves...
Gaussian normalizer: The Gaussian normalizer rescales the values of each feature to have mean 0 and variance 1. This is done by computing the mean and the variance of each feature. For each instance, the mean value is subtracted, and the result divided by the square root of the variance ...
\(\square \) 7 UniBench evaluation In this section, we introduce the evaluation of UniBench. Specifically, Sect. 7.1 presents the experiments of data generation, and Sect. 7.2 show the results of parameter curation. 7.1 Data generation For the experimental setup, we generate the synthetic data...
Prediction errors for are reported as root-mean-square errors (RMSEs) from the training and test sets, i.e. all the points on the curve not used for training. Plots (a) and (b) show ordinary GP regressions with five and ten training points, respectively. With five training points, the...
It compares the mean square error (MSE) of the prediction \(\widetilde{{{\bf{y}}}\) from the model with the MSE of the baseline that takes the constant value \(\bar{{{\bf{y}}}\) as the prediction. It takes a value from \((-\infty,\,1]\) and equals one when \(\widetilde...
window before the Wnt pulse (Fig.2n). Gastruloids imaged post-Wnt activation exhibited the longest track length (Fig.2o). Evaluation of the 3D mean-square displacement (m.s.d.3D) suggested an increased speed and a change in migration behavior of cells tracked from 90 h onward (Fig.2p...