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Found 6 papers, 4 papers with code
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
We also propose a new mixture-of-experts (MoE) based decoder, which treats the feature maps from the encoder as experts and selects a suitable set of expert features to predict the label for each pixel.
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images
Thus, it is not ideal to apply most existing segmentation methods as they are designed for either 2D or 3D images.
Epsilon Consistent Mixup: Structural Regularization with an Adaptive Consistency-Interpolation Tradeoff
In this paper we propose $\epsilon$-Consistent Mixup ($\epsilon$mu).
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
Instead, we would prefer a method that allows an agent's state at one time to directly affect another agent's state at a future time.
Ranked #10 on
Trajectory Prediction
on ETH/UCY
Semi-Supervised Cervical Dysplasia Classification With Learnable Graph Convolutional Network
In this paper, we propose a novel and more flexible GCN model with a feature encoder that adaptively updates the adjacency matrix during learning and demonstrate that this model design leads to improved performance.
Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks
Aspect Based Sentiment Analysis, PyTorch Implementations.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
