전체 글236 [2023-2] 박태호 - Tacotron: Towards End-to-End Speech Synthesis 2017년도 구글에서 발표한 논문으로, 문자(character)로부터 직접 음성을 합성하는 end-to-end TTS 모델 Tacotron을 제시한다. 논문 원본 링크 https://arxiv.org/abs/1703.10135 Tacotron: Towards End-to-End Speech Synthesis A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module. Building these components often requires extensive domain expertise a.. 2024. 1. 29. [2023-2] 주서영 - EEG2IMAGE: Image Reconstruction from EEG Brain Signals EEG2IMAGE: Image Reconstruction from EEG Brain Signals Reconstructing images using brain signals of imagined visuals may provide an augmented vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) technology. The recent progress in deep learning has boosted the study area of synth arxiv.org GitHub - prajwalsingh/EEG2Image: EEG2IMAGE: Image Reconstruction from EEG Br.. 2024. 1. 24. [2023-2] 김경훈 - Latent Consistency Models: Synthesizing High-Resolution Images wi 원본 논문 링크 : https://arxiv.org/abs/2310.04378 Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step InferenceLatent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and leads to slow generation. Inspired by Consistency Models (song et al.), we proparxiv.org PD.. 2024. 1. 23. [2023-2] 김동한 - NeuralProphet: Explainable Forecasting at Scale 논문 소개 : https://paperswithcode.com/paper/neuralprophet-explainable-forecasting-at 논문 링크 : https://arxiv.org/pdf/2111.15397v1.pdf 이전 prophet논문 리뷰: https://outta.tistory.com/19 NeuralProphet: Explainable Forecasting at Scale 0. Abstract - facebook prophet의 후속 모델 - 설명 가능하고 확장 가능 / 사용자 친화적 예측 프레임워크 - 시계열 데이터에서의 적용 - 기존의 prophet은 근접 미래를 예측하기 위해 필수적인 지역적 맥락이 없다면, 적용 및 확장이 어려움. - nerual prophet 모델은 pyt.. 2024. 1. 23. 이전 1 ··· 51 52 53 54 55 56 57 ··· 59 다음
