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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/dniku/perceptual-gradient-networks

Deep Image Prior

https://github.com/dome272/wuerstchen

A Novel Sampling Scheme for Text- and Image-Conditional Image Synthesis in Quantized Latent Spaces

https://github.com/donghoney0416/DeFT-AN

DeFT-AN: Dense Frequency-Time Attentive Network for Multichannel Speech Enhancement

https://github.com/dongyan007/Pretrained-IPT-main-master

Pre-Trained Image Processing Transformer

https://github.com/dopplerchase/cira-diff

Denoising Diffusion Probabilistic Models

https://github.com/dsl-lab/swingnn

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation

https://github.com/dsl-lab/symmetricdiffusers

SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups

https://github.com/dslisleedh/NAFNet-flax

Simple Baselines for Image Restoration

https://github.com/dslisleedh/NAFNet-tensorflow2

Simple Baselines for Image Restoration

https://github.com/dsubuntu/scie

Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?

https://github.com/dynamicslab/langevin-regression

Sparse learning of stochastic dynamic equations

https://github.com/dzq84/MusicScore-script

Denoising Diffusion Implicit Models

https://github.com/earthspecies/audio-embeddings

Audio Word2Vec: Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Autoencoder

https://github.com/edward-reehorst/On_RED

Regularization by Denoising: Clarifications and New Interpretations

https://github.com/egkang-luis/burstm

Burstormer: Burst Image Restoration and Enhancement Transformer

https://github.com/elras/SoftsegmentNeurons

Modular proximal optimization for multidimensional total-variation regularization

https://github.com/emanueledalsasso/SAR2SAR

SAR2SAR: a semi-supervised despeckling algorithm for SAR images

https://github.com/envision-research/lotus

Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

https://github.com/eoinoreilly30/seeing-in-the-dark

Learning to See in the Dark

https://github.com/era-dorta/tf_mvg

Structured Uncertainty Prediction Networks

https://github.com/ericl122333/patchdiffusion-pytorch

Perception Prioritized Training of Diffusion Models

https://github.com/ericoldgren/kex---ct-reconstruction

2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning

https://github.com/ethz-spylab/diffusion_denoised_smoothing

(Certified!!) Adversarial Robustness for Free!

https://github.com/evtaktasheva/dependency_extraction

Multilingual Denoising Pre-training for Neural Machine Translation

https://github.com/explainingai-code/DDPM-Pytorch

Denoising Diffusion Probabilistic Models

https://github.com/explainingai-code/StableDiffusion-PyTorch

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/exploration-lab/iitk-semeval-2024-task-1

TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/fabidicia/DANAE

DANAE: a denoising autoencoder for underwater attitude estimation

https://github.com/facebookresearch/DomainBed

Domain Generalization for Object Recognition with Multi-task Autoencoders

https://github.com/facebookresearch/GENRE

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/facebookresearch/bart_ls

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/facebookresearch/flowmm

Crystal Structure Prediction by Joint Equivariant Diffusion

https://github.com/facebookresearch/w2ot

Generative Modeling with Optimal Transport Maps

https://github.com/fanbeatsman/tensorflow-quick-start-image-processing-focus-

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/farrowlab/Neuron-Softsegmentation

Modular proximal optimization for multidimensional total-variation regularization

https://github.com/fashn-AI/tryondiffusion

Simple diffusion: End-to-end diffusion for high resolution images

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.