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11/30/2022
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification
The main challenge for fine-grained few-shot image classification is to ...
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11/14/2021
Numerical Analysis of the Multiple Scattering Theory for Electronic Structure Calculations
The multiple scattering theory (MST) is one of the most widely used meth...
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07/31/2021
Unified analysis of finite-size error for periodic Hartree-Fock and second order Møller-Plesset perturbation theory
Despite decades of practice, finite-size errors in many widely used elec...
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05/17/2021
Deep Metric Learning for Few-Shot Image Classification: A Selective Review
Few-shot image classification is a challenging problem which aims to ach...
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02/18/2021
Staggered mesh method for correlation energy calculations of solids: Second order Møller-Plesset perturbation theory
The calculation of the MP2 correlation energy for extended systems can b...
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01/25/2021
ATRM: Attention-based Task-level Relation Module for GNN-based Few-shot Learning
Recently, graph neural networks (GNNs) have shown powerful ability to ha...
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11/29/2020
BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification
Few-shot learning for fine-grained image classification has gained recen...
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10/12/2020
CC-Loss: Channel Correlation Loss For Image Classification
The loss function is a key component in deep learning models. A commonly...
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06/27/2020
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification
Despite achieving state-of-the-art performance, deep learning methods ge...
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05/22/2020
A Concise Review of Recent Few-shot Meta-learning Methods
Few-shot meta-learning has been recently reviving with expectations to m...
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04/20/2020
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer
A deep neural network of multiple nonlinear layers forms a large functio...
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02/11/2020
