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Found 10 papers, 6 papers with code
Observation, Analysis, and Solution: Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-Training
In this paper, we question if the extremely simple ViTs' fine-tuning performance with a small-scale architecture can also benefit from this pre-training paradigm, which is considerably less studied yet in contrast to the well-established lightweight architecture design methodology with sophisticated components introduced.
HomoGenius: a Foundation Model of Homogenization for Rapid Prediction of Effective Mechanical Properties using Neural Operators
Homogenization is an essential tool for studying multiscale physical phenomena.
ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking
To this end, we non-uniformly resize the cropped image to have a smaller input size while the resolution of the area where the target is more likely to appear is higher and vice versa.
SBSM-Pro: Support Bio-sequence Machine for Proteins
We introduce the Support Bio-Sequence Machine for Proteins (SBSM-Pro), a model purpose-built for the classification of biological sequences.
Optimizing Carbon Storage Operations for Long-Term Safety
In this study, we address these issues by modeling the decision-making process for carbon storage operations as a partially observable Markov decision process (POMDP).
DCEM-PINNs: A deep complementary energy method for solid mechanics
The results demonstrate that DCEM outperforms DEM in terms of stress accuracy and efficiency and has an advantage in dealing with complex displacement boundary conditions, which is supported by theoretical analyses and numerical simulations.
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations
The boundary integral equations are employed to transfer all the unknowns to the boundary, then the unknowns are approximated using neural networks and solved through a training process.
A POMDP Model for Safe Geological Carbon Sequestration
This POMDP model can be used as a test bed to drive the development of novel decision-making algorithms for CCS operations.
PETS-SWINF: A regression method that considers images with metadata based Neural Network for pawpularity prediction on 2021 Kaggle Competition "PetFinder.my"
In order to better adopt stray animals, scoring the pawpularity (cuteness) of stray animals is very important, but evaluating the pawpularity of animals is a very labor-intensive thing.
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
The advantage of the proposed method is higher efficiency, more accurate, and less hyperparameters than the strong form PINN with subdomains.
