Search Results - "https :// github"

Quantum Deep Descriptor: Physically Informed Transfer Learning from Small Molecules to Polymers by Tsubaki, Masashi, Mizoguchi, Teruyasu

“…In this study, we propose a physically informed transfer learning approach for materials informatics (MI) using a quantum deep descriptor (QDD) obtained from…”
Get more information

Image Deblurring by Exploring In-Depth Properties of Transformer by Liang, Pengwei, Jiang, Junjun, Liu, Xianming, Ma, Jiayi

“…Image deblurring continues to achieve impressive performance with the development of generative models. Nonetheless, there still remains a displeasing problem…”
Get full text

TSM: Temporal Shift Module for Efficient Video Understanding by Lin, Ji, Gan, Chuang, Han, Song

“…The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost. Conventional 2D…”
Get full text

Image Processing and Machine Learning for Automated Identification of Chemo-/Biomarkers in Chromatography-Mass Spectrometry by Jirayupat, Chaiyanut, Nagashima, Kazuki, Hosomi, Takuro, Takahashi, Tsunaki, Tanaka, Wataru, Samransuksamer, Benjarong, Zhang, Guozhu, Liu, Jiangyang, Kanai, Masaki, Yanagida, Takeshi

“…We present a method named NPFimg, which automatically identifies multivariate chemo-/biomarker features of analytes in chromatography-mass spectrometry (MS)…”
Get more information

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides by Zhang, Shengli, Jing, Yuanyuan, Liang, Yunyun

“…The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe acute respiratory…”
Get more information

Can We Automate Scientific Reviewing? by Yuan, Weizhe, Liu, Pengfei, Neubig, Graham

“…The rapid development of science and technology has been accompanied by an exponential growth in peer-reviewed scientific publications. At the same time, the…”
Get full text

PVT v2: Improved baselines with Pyramid Vision Transformer by Wang, Wenhai, Xie, Enze, Li, Xiang, Fan, Deng-Ping, Song, Kaitao, Liang, Ding, Lu, Tong, Luo, Ping, Shao, Ling

“…Transformers have recently lead to encouraging progress in computer vision. In this work, we present new baselines by improving the original Pyramid Vision…”
Get full text

MultiGran-SMILES: multi-granularity SMILES learning for molecular property prediction by Jiang, Jing, Zhang, Ruisheng, Zhao, Zhili, Ma, Jun, Liu, Yunwu, Yuan, Yongna, Niu, Bojuan

“…Extracting useful molecular features is essential for molecular property prediction. Atom-level representation is a common representation of molecules,…”
Get full text

DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification by Zhang, Hongrun, Meng, Yanda, Zhao, Yitian, Qiao, Yihong, Yang, Xiaoyun, Coupland, Sarah E., Zheng, Yalin

“…Multiple instance learning (MIL) has been increasingly used in the classification of histopathology whole slide images (WSIs). However, MIL approaches for this…”
Get full text

NeatIBP 1.0, a package generating small-size integration-by-parts relations for Feynman integrals by Wu, Zihao, Boehm, Janko, Ma, Rourou, Xu, Hefeng, Zhang, Yang

Get full text

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search by Wu, Bichen, Keutzer, Kurt, Dai, Xiaoliang, Zhang, Peizhao, Wang, Yanghan, Sun, Fei, Wu, Yiming, Tian, Yuandong, Vajda, Peter, Jia, Yangqing

“…Designing accurate and efficient ConvNets for mobile devices is challenging because the design space is combinatorially large. Due to this, previous neural…”
Get full text

Domain Adaptation for Semantic Segmentation With Maximum Squares Loss by Chen, Minghao, Xue, Hongyang, Cai, Deng

“…Deep neural networks for semantic segmentation always require a large number of samples with pixel-level labels, which becomes the major difficulty in their…”
Get full text

Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting by Yi, Zili, Tang, Qiang, Azizi, Shekoofeh, Jang, Daesik, Xu, Zhan

“…Recently data-driven image inpainting methods have made inspiring progress, impacting fundamental image editing tasks such as object removal and damaged image…”
Get full text

Bayesian optimization package: PHYSBO by Motoyama, Yuichi, Tamura, Ryo, Yoshimi, Kazuyoshi, Terayama, Kei, Ueno, Tsuyoshi, Tsuda, Koji

“…PHYSBO (optimization tools for PHYSics based on Bayesian Optimization) is a Python library for fast and scalable Bayesian optimization. It has been developed…”
Get full text

A wave-shaped CNN for marine-raft aquaculture-area extraction in SAR images by Yanjun, Guo, Yunyan, Du, Ming, Yan, Ting, Xie, Moyun, Liu, Nan, Wang

“…This paper introduces an innovative deep convolutional neural network, the wave-shaped CNN, tailored for the robust extraction of a marine-raft aquaculture…”
Get full text

Train in Germany, Test in the USA: Making 3D Object Detectors Generalize by Wang, Yan, Chen, Xiangyu, You, Yurong, Li, Li Erran, Hariharan, Bharath, Campbell, Mark, Weinberger, Kilian Q., Chao, Wei-Lun

“…In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike. While…”
Get full text

Tropical Feynman integration in the Minkowski regime by Borinsky, Michael, Munch, Henrik J., Tellander, Felix

“…We present a new computer program, feyntrop, which uses the tropical geometric approach to evaluate Feynman integrals numerically. In order to apply this…”
Get full text

Activation functions in deep learning: A comprehensive survey and benchmark by Dubey, Shiv Ram, Singh, Satish Kumar, Chaudhuri, Bidyut Baran

“…Neural networks have shown tremendous growth in recent years to solve numerous problems. Various types of neural networks have been introduced to deal with…”
Get full text

QuOCS: The quantum optimal control suite by Rossignolo, Marco, Reisser, Thomas, Marshall, Alastair, Rembold, Phila, Pagano, Alice, Vetter, Philipp J., Said, Ressa S., Müller, Matthias M., Motzoi, Felix, Calarco, Tommaso, Jelezko, Fedor, Montangero, Simone

“…Quantum optimal control includes a family of pulse-shaping algorithms that aim to unlock the full potential of a variety of quantum technologies. The Quantum…”
Get full text

XLB: A differentiable massively parallel lattice Boltzmann library in Python by Ataei, Mohammadmehdi, Salehipour, Hesam

“…The lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational…”
Get full text