Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning de
In PISTE, the conventional, data-driven attention mechanism is replaced with physics-driven dynamics that steers the positioning of amino acid residues along the gradient field of their interactions. This allows navigating the intricate landscape of biosequence interactions intelligently, leading to ...
Notably, the performance was stably improved the same as in the experiments without adding these other class data (Fig. 5a), suggesting the robustness of the proposed framework to assure that the AI model is not confused by these unseen classes to the initial model trained only with normal ...
Problems involving geometric data arise in physics, chemistry, robotics, computer vision, and many other fields. Such data can take numerous forms, such as points, direction vectors, translations, or rotations, but to date there is no single architecture that can be applied to such a wide varie...
Specifically, we use 12 different scales ranging from 32 to 384 pixels and 3 aspect ratios (0.5, 1.0, 1.5) to define a total of 36 anchors. We then project all 3D ground truth boxes to the 2D space and calculate its intersection over union (IoU) with each 2D anchor and assign the ...
import torch import torch.nn as nn class DecoderLayer(nn.Module): def __init__(self, d_model, num_heads, d_ff, dropout): super(DecoderLayer, self).__init__() # 多头自注意力机制(解码器自注意力) self.self_attention = nn.MultiheadAttention(d_model, num_heads, dropout=dropout) # ...
The comparison of accuracy for each class of reactions was presented in Fig. 6. Our best model showed excellent results, outperforming the state-of-the-art Self-Corrected Transformer19. Functional group interconversion and addition, as well as carbon–carbon bond formation were the most difficult ...
He co-authored several papers published in top-tier journals and conferences such as Computer Physics Communications and WACV. Mariana-Iuliana Georgescu is a Ph.D. student at the Faculty of Mathematics and Computer Science, University of Bucharest. She received the B.Sc. degree from the Faculty ...
In physics11, the FT is a powerful tool used to decompose complex physical systems in a given space, such as position, into a more straightforward formulation in another, often momentum space. This transformation simplifies the analysis, for example, of waveforms in quantum mechanics and ...
The ongoing progress in MLFF development has resulted in a wide range of increasingly sophisticated model architectures aiming to improve the extrapolation behavior. Among these, message passing neural networks (MPNNs)9,12,34have emerged as a particularly effective class of architectures. MPNNs can be...