2 citations · 4 across the 7 of their papers we have counts for
7 papers
Graph Contrastive Learning with Implicit Augmentations
Huidong Liang, Xingjian Du, Bilei Zhu +3
Existing graph contrastive learning methods rely on augmentation techniques based on random perturbations (e.g., randomly adding or dropping edges and nodes). Nevertheless, alterin…
TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music
Ke Chen, Shuai Yu, Cheng-i Wang +3
Singing melody extraction is an important problem in the field of music information retrieval. Existing methods typically rely on frequency-domain representations to estimate the s…
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection
Ke Chen, Xingjian Du, Bilei Zhu +3
Audio classification is an important task of mapping audio samples into their corresponding labels. Recently, the transformer model with self-attention mechanisms has been adopted…
Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data
Ke Chen, Xingjian Du, Bilei Zhu +3
Deep learning techniques for separating audio into different sound sources face several challenges. Standard architectures require training separate models for different types of a…
Learning-Based Video Game Development in MLP@UoM: An Overview
Ke Chen
In general, video games not only prevail in entertainment but also have become an alternative methodology for knowledge learning, skill acquisition and assistance for medical treat…
On the Use of Sparse Filtering for Covariate Shift Adaptation
Fabio Massimo Zennaro, Ke Chen
In this paper we formally analyse the use of sparse filtering algorithms to perform covariate shift adaptation. We provide a theoretical analysis of sparse filtering by evaluating…
Learning-Based Procedural Content Generation
Jonathan Roberts, Ke Chen
Procedural content generation (PCG) has recently become one of the hottest topics in computational intelligence and AI game researches. Among a variety of PCG techniques, search-ba…