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Found 11 papers, 2 papers with code
WAE_RN: Integrating Wasserstein Autoencoder and Relational Network for Text Sequence
In spite of the success of pre-trained language model in many NLP tasks, the learned text representation only contains the correlation among the words in the sentence itself and ignores the implicit relationship between arbitrary tokens in the sequence.
RedCore: Relative Advantage Aware Cross-modal Representation Learning for Missing Modalities with Imbalanced Missing Rates
Multimodal learning is susceptible to modality missing, which poses a major obstacle for its practical applications and, thus, invigorates increasing research interest.
Rapid online solution of inverse heat transfer problem by ANN-based extended Kalman smoothing algorithm
Digital twin is a modern technology for many advanced applications.
A Reinforcement Learning Framework for Online Speaker Diarization
Our approach considers speaker diarization as a fully online learning problem of the speaker recognition task, where the agent receives no pretraining from any training set before deployment, and learns to detect speaker identity on the fly through reward feedbacks.
RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment
Therefore, we propose a Progressive Reinforcement learning based Instance Discarding module (termed as PRID) to progressively remove quality-irrelevant/negative instances for CCTA VIQA.
Steady-state nonlinearity of open-loop reset systems
In this paper, we introduce a new representation for open-loop reset systems.
Frequency-domain analysis for reset systems using pulse-based model
In this paper, a new analytical technique for reset controllers is proposed to break the limitations.
Geodesic Paths for Image Segmentation with Implicit Region-based Homogeneity Enhancement
Minimal paths are regarded as a powerful and efficient tool for boundary detection and image segmentation due to its global optimality and the well-established numerical solutions such as fast marching method.
Speaker Diarization as a Fully Online Learning Problem in MiniVox
We proposed a novel machine learning framework to conduct real-time multi-speaker diarization and recognition without prior registration and pretraining in a fully online learning setting.
Hierarchical Optimization Time Integration for CFL-rate MPM Stepping
We propose Hierarchical Optimization Time Integration (HOT) for efficient implicit time-stepping of the Material Point Method (MPM) irrespective of simulated materials and conditions.
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Tree Recognition APP of Mount Tai Based on CNN
Mount Tai has abundant sunshine, abundant rainfall and favorable climatic conditions, forming dense vegetation with various kinds of trees.
