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Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changin ...

2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

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Graph-to-Graph Transformer for Transition-based Dependency Parsing

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Transformer Models for Vision

Source-Free Open-Set Domain Adaptation for Histopathological Images via Distilling Self-Supervised Vision Transformer

Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

A new age in protein design empowered by deep learning

Modeling Structured Data in Attention-based Models

Graph Chatbot

Chat with Graph Search

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Transformer Models for Vision

Source-Free Open-Set Domain Adaptation for Histopathological Images via Distilling Self-Supervised Vision Transformer

Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

A new age in protein design empowered by deep learning

Modeling Structured Data in Attention-based Models