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3D Architecture

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/vinairesearch/bartpho

공식 코드

BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese

https://github.com/vinairesearch/phomt

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PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation

https://github.com/vinairesearch/sa-dpm

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On Inference Stability for Diffusion Models

https://github.com/vineetjain96/merlin

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Learning to Reach Goals via Diffusion

https://github.com/vinesmsuic/ipainter-diffusion

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Intelligent Painter: Picture Composition With Resampling Diffusion Model

https://github.com/vinhsuhi/ld3

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Learning to Discretize Denoising Diffusion ODEs

https://github.com/vint-1/chipdiffusion

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Chip Placement with Diffusion Models

https://github.com/vios-s/Inference_Denoising_MRI_Recon

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Inference Stage Denoising for Undersampled MRI Reconstruction

https://github.com/vis-opt-group/bl

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Bilevel Fast Scene Adaptation for Low-Light Image Enhancement

https://github.com/vishwa91/deepir

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Thermal Image Processing via Physics-Inspired Deep Networks

https://github.com/visinf/n3net

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Neural Nearest Neighbors Networks

https://github.com/visionresearchlab/synthset

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SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision Agriculture

https://github.com/visualaikhu/monowad

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MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection

https://github.com/vita-epfl/deposit

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A generic diffusion-based approach for 3D human pose prediction in the wild

https://github.com/vivekkumartri/mcddpm

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MCDDPM: Multichannel Conditional Denoising Diffusion Model for Unsupervised Anomaly Detection in Brain MRI

https://github.com/vivsivaraman/designaudiopriors

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On the Design of Deep Priors for Unsupervised Audio Restoration

https://github.com/vlogroup/pogmdm

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Product of Gaussian Mixture Diffusion Models

https://github.com/vmboehm/pae-ablation

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Probabilistic Autoencoder

https://github.com/vmtenorio/neighborhoodgf

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A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters

https://github.com/vmtenorio/robust_gnn

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Robust Graph Neural Network based on Graph Denoising

https://github.com/voilalab/inr-benchmark

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Grids Often Outperform Implicit Neural Representations

https://github.com/voletiv/mcvd-pytorch

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MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation

https://github.com/vpronina/DeepWienerRestoration

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Microscopy Image Restoration with Deep Wiener-Kolmogorov filters

https://github.com/vpx-ecnu/find-website

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FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion Models

https://github.com/vsuarezpaniagua/3-phase_finetuning

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Combining Denoising Autoencoders with Contrastive Learning to fine-tune Transformer Models

https://github.com/vut-hfut/eulermormer

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EulerMormer: Robust Eulerian Motion Magnification via Dynamic Filtering within Transformer

https://github.com/vvvm23/sundae-vqgan

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Megapixel Image Generation with Step-Unrolled Denoising Autoencoders

https://github.com/vzyrianov/lidargen

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Learning to Generate Realistic LiDAR Point Clouds

https://github.com/wadieskaf/denoising_architecture_time_series_paper

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Denoising Architecture for Unsupervised Anomaly Detection in Time-Series

https://github.com/wang-xiaodingdd/lgbpn

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LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising

https://github.com/wang-yanting/tracllm

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TracLLM: A Generic Framework for Attributing Long Context LLMs

https://github.com/wangelik/TraVaGen

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Releasing Differentially Private Event Logs Using Generative Models

https://github.com/wangguanan/denoiserep

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DenoiseRep: Denoising Model for Representation Learning

https://github.com/wanghailin97/Guaranteed-Tensor-Recovery-Fused-Low-rankness-and-Smoothness

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Guaranteed Tensor Recovery Fused Low-rankness and Smoothness

https://github.com/wangjiangshan0725/cove

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COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing

https://github.com/wangjiyuan9/d4rd

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Digging into contrastive learning for robust depth estimation with diffusion models

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