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In this article we consider two different extensions of SM to attain the dark sector. In the first one we extend SM to Type-I 2HDM with-oddSU(2) doublet that constitutes the dark sector and the scenario is known as inert Higgs doublet (IDM). In the second case we consider the dark...
margin(float,可选的) -一个非负边距,表示损失为 0 所需的正负距离之间的最小差异。较大的边距会惩罚负样本相对于正样本距离锚点不够远的情况。默认值:。 swap(bool,可选的) -是否使用 V. Balntas、E. Riba 等人在论文Learning shallow convolutional feature descriptors with triplet losses中说明的距离交换。
掩码中的元素b_i^{r_i}或b_j^{r_j} 定义为: 其中,\text{cum_sum}(r_i)表示到元素b_i为止的累积权重,这个元素在按降序排列的令牌权重中排名为r_i第r_i位,τ是一个固定的阈值,表示需要被掩码的特征比例。 然后,我们推导出加权的全局文本特征: 以及相应的掩码文本特征: 其中,公式15-16中的...
(torch.Tensor): feature matrix with shape (batch_size, feat_dim).targets (torch.LongTensor): ground truth labels with shape (num_classes)."""iftargets==None:targets=self.targetsn=inputs.size(0)# Compute pairwise distance, replace by the official when mergeddist=torch.pow(inputs,2).sum...
Chandhok, S.“Triplet Loss with Keras and TensorFlow,”PyImageSearch, P. Chugh, A. R. Gosthipaty, S. Huot, K. Kidriavsteva, R. Raha, and A. Thanki, eds., 2023,https://pyimg.co/2try0 @incollection{Chandhok_2023_TLwK+TF, author = {Shivam Chandhok}, title = {Triplet Loss ...
Understanding the pairing symmetry is a crucial theoretical aspect in the study of unconventional superconductivity for interpreting experimental results. Here we study superconductivity of electron systems with both spin and pseudospin-1/2 degrees of fr
pytorch中通过 torch.nn.TripletMarginLoss 类实现，也可以直接调用 F.triplet_margin_loss 函数。 size_average 与 reduce 已经弃用。reduction有三种取值 mean , sum , none ，对应不同的返回 。 默认为 mean ，对应于一般情况下整体 的计算。该类默认使用如下距离函数， 默认为2，对应...
One considers the time evolution of a (non-stationary) wavefunction, represented as a sum of two states Ψ1 and Ψ2 with time factors exp –iE1t/ħ and exp –iE2t/ħ, respectively: the square of the wavefunction then oscillates with period (30)τ=ℏE1−E2, which is a ‘...
They found that Bi-Gated Recurrent Units (GRUs) [30] with self-attention performed the best. One popular way of training Siamese networks is to use triplets [20]. Sumbul et al. [31] provided a solution for efficient triplet sampling on multi-label image data. However, the gained ...