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Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.
Official Pytorch implementation of the paper Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance (accepted to ICLR 2023)
Official PyTorch implementation of SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization (INTERSPEECH 2023 Oral Presentation)
Personalized and Reliable Predictive Models for Healthcare (의료 데이터 기반 신뢰 가능한 개인화된 예측(진단) 모델)
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)
Implementations for "Trimming the ℓ₁ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning" Published on ICML 2019
This repository is the official PyTorch implementation of "Distilling Linguistic Context for Language Model Compression" by GeondoPark, Gyeongman Kim and Eunho Yang.
An official implementation of "Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding" (CVPR 2023) in PyTorch.
Must read research papers and links on quantum compiler and system
[CVPR 2024] Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis
An official implementation of "AZ-NAS: Assembling Zero-Cost Proxies for Network Architecture Search" (CVPR 2024) in PyTorch.
An official implementation of "ACLS:Adaptive and Conditional Label Smoothing for Network Calibration" (ICCV 2023) in PyTorch.
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification (ICLR'22)
A collection of resources and papers on Diffusion Models
The repo for studying and sharing diffusion models.
Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)
비트코인, 알트코인 자동 매매 프로그램 (업비트용), 변동성 돌파 전략을 이용한 가상화폐, 업비트 자동 매매 프로그램
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
백엔드 개발자로 입사를 준비하며 받았던 질문, 예상했던 질문, 인터넷 참고한 질문(CC BY-NC)