From my understanding, the output in the BCEWithLogitsLoss are the 6 tensors of the batch, and he predicts "normal" if the output tensor is negative and "abnormal" if positive. But they're stuck in negative so they're all predicted normal. Since my goal is to make a "probability ...
First, introduce a continuous density ρe to connect the specific parameters of two materials: 0≤ρe≤1, and then add penalization on intermediate density to let the optimized object converge to discrete structure, because the intermediate density has no practical meaning in physics. For example,...
Technically, the Kullback–Leibler (KL) divergence is used in our research to define the first loss of LKL, and the Cross-Entropy (CE) is used to define the second loss of LCE. Before writing the LKD in detail, we first define the softmax output of a deep neural network as (5.12)p...
where\(\varphi\)is the size ratio of the two species of NPs,\(\epsilon\)is the relative strength of interparticle interaction\({\varepsilon }_{11}\)to surface tension,\(\chi\)is the ratio of the difference in the surface energy of NP 1 with the two fluids to the surface tension be...
In a system with finite precision, the two values are bound to converge; and we will lose all information about the sequence from the point at which the two values converged. To avoid this situation, we need to rescale the interval. However, we have to do it in a way that will ...
The wave direction is diverted if the wave ray is abnormal to the bottom measurement. It is noted that the wave rays converge in shallow areas and diverge in deep areas [28]. In this algorithm, when the waves whose heights reach to zero, the refraction operator is applied on those waves...
The wave direction is diverted if the wave ray is abnormal to the bottom measurement. It is noted that the wave rays converge in shallow areas and diverge in deep areas [28]. In this algorithm, when the waves whose heights reach to zero, the refraction operator is applied on those waves...
Without loss of generality, we assume that N is zero-mean; i.e., 𝑁∼𝒩(0,𝜎2)N∼N(0,σ2). Denote the signal-to-noise ratio (SNR) between the input signal and noise as 𝛾≜𝑝/𝜎2γ≜p/σ2. Figure 1. The Gaussian channel with binary inputs and quantized/un...
are the ratios of occurrences of zeros and ones within the bitstring C k ( N ) , and the unit of entropy (3) is a bit. Definition 1. A bitstring assembly index, a ( N ) , is the smallest number of steps, s, required to assemble a bitstring, C k ( N ) , of length N ...
Assembly theory (AT) [1,2,3,4,5,6,7] provides a distinctive complexity measure superior to established complexity measures used in information theory, such as Shannon entropy or Kolmogorov complexity [1,5]. AT does not alter the fundamental laws of physics [6]. Instead, it redefines objects...