Abstract: Mamba and its variants excel at modeling long-range dependencies with linear computational complexity, making them effective for diverse vision tasks. However, Mamba’s reliance on unfolding ...

@InProceedings{Saijo2024_TFLoco, author = {Saijo, Kohei and Wichern, Gordon and Germain, Fran\c{c}ois G. and Pan, Zexu and {Le Roux}, Jonathan}, title = {TF-Locoformer: Transformer with Local Modeling ...

PyTorch training and evaluation code for RETR (Radar dEtection TRansformer). RETR inherits the advantages of DETR, eliminating the need for hand-crafted components for object detection and ...

Molecular generation models, especially chemical language model (CLM) utilizing SMILES, a string representation of compounds, face limitations in handling large and complex compounds while maintaining ...

Step 4: Implementing Positional Encoding Since transformers don’t process data sequentially like RNNs, we need to tell the model the order of words. Positional encoding adds a unique vector to each ...

Since its breakthrough in 2017 with the “Attention Is All You Need” paper, the Transformer model has redefined natural language processing. At its core lie two specialized components: the encoder and ...

Remote visible-shortwave infrared (VSWIR) imaging spectrometers such as Earth surface Mineral dust source InvesTigation (EMIT) are enabling a new area of quantitative Earth Science by collecting ...

Abstract: As an indispensable part of geophysical exploration, seismic inversion can obtain the properties of subsurface media based on seismic data and available well-log information. With the ...

Birds-Eye-View (BEV) maps provide an accurate representation of sensory cues present in the surroundings, including dynamic and static elements. Generating a semantic representation of BEV maps can be ...

An increasing number of studies have been devoted to electroencephalogram (EEG) identity recognition since EEG signals are not easily stolen. Most of the existing studies on EEG person identification ...