[신입생세미나] Frequency Domain Representations(part1)
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220407_신입생세미나_이성규_Ch3_1 Fundamentals of Human Speech Production 220527_신입생세미나_이성규_Ch7_1_Frequency Domain Represenations
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[논문리뷰세미나] Evidential Deep Learning to Quantify Classification Uncertainty [pdf] 이성규_Evidential Deep Learning to Quantify Classification Uncertainty.pdf [ppt] 이성규_Evidential Deep Learning to Quantify Classification Uncertainty.pptx
[논문리뷰 세미나] Multivariate, Multi-frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in Conversation [ppt] [공유용]이성규_Multivariate, Multi-Frequency and Multimodal.pptx [pdf] [공유용]이성규_Multivariate, Multi-Frequency and Multimodal.pdf
[논문리뷰] Denoising Diffusion Probabilistic Models 논문 리뷰 해봤습니다. [ppt] [발표자료.`22.12.02]이성규_DDPM
논문정보 논문제목: Multivariate, Multi-frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in Conversation (링크) 논문 Overview GNN (Graph Neural Network)을 활용한 대화형 감정인식 (ERC: Emotion Recognition in Conversation)이 모델들이 있다. 기존의 GNN based ERC 모델은 node 사이의 pairwise 관계만 보고 있어 node사이의 복잡한 관계를 알기 어려운 구조라는 한계가 있다는 점을 본 논문에서 지적하고 … Read more