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Found 8 papers, 4 papers with code
Utilizing Computer Vision for Continuous Monitoring of Vaccine Side Effects in Experimental Mice
By deploying a computer vision system, our research aims to improve the efficiency and accuracy of vaccine safety assessments.
Evaluating Cognitive and Neuropsychological Assessments -- A Comprehensive Review
Cognitive impairments in older adults represent a significant public health concern, necessitating accurate diagnostic and monitoring strategies.
Immunogenic cell death triggered by pathogen ligands via host germ line-encoded receptors
In response to infections, host cells dictate a variety of cell death pathways, including apoptosis, pyroptosis, necrosis, and lysosomal cell death, which are essential for amplifying immune responses and controlling pathogen dissemination.
Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision
Specifically, we introduce a novel method that enhances the learning of embeddings in SR through the supervision of modality correlations.
UNO-DST: Leveraging Unlabelled Data in Zero-Shot Dialogue State Tracking
Previous zero-shot dialogue state tracking (DST) methods only apply transfer learning, ignoring unlabelled data in the target domain.
A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems
However, not all CRS approaches use human conversations as their source of interaction data; the majority of prior CRS work simulates interactions by exchanging entity-level information.
SwinLSTM:Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM
In this paper, we propose a new recurrent cell, SwinLSTM, which integrates Swin Transformer blocks and the simplified LSTM, an extension that replaces the convolutional structure in ConvLSTM with the self-attention mechanism.
SwinLSTM: Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM
In this paper, we propose a new recurrent cell, SwinLSTM, which integrates Swin Transformer blocks and the simplified LSTM, an extension that replaces the convolutional structure in ConvLSTM with the self-attention mechanism.
Ranked #7 on
Video Prediction
on Moving MNIST
