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Mamba

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

https://github.com/aeromamba-super-resolution/aeromamba

공식 코드

AEROMamba: An efficient architecture for audio super-resolution using generative adversarial networks and state space models

https://github.com/ahappyyang/GraphMamba

공식 코드

GraphMamba: An Efficient Graph Structure Learning Vision Mamba for Hyperspectral Image Classification

https://github.com/ai4sd/multiscale-byte-lm

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Multiscale Byte Language Models -- A Hierarchical Architecture for Causal Million-Length Sequence Modeling

https://github.com/aiot-mlsys-lab/famba-v

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Famba-V: Fast Vision Mamba with Cross-Layer Token Fusion

https://github.com/aleksandarpetrov/lsrl

공식 코드

Universal In-Context Approximation By Prompting Fully Recurrent Models

https://github.com/alexhe101/pan-mamba

공식 코드

Pan-Mamba: Effective pan-sharpening with State Space Model

https://github.com/alexyangxx/colormamba

공식 코드

ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with Mamba

https://github.com/alexzou14/wave-mamba

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Wave-Mamba: Wavelet State Space Model for Ultra-High-Definition Low-Light Image Enhancement

https://github.com/ali-meh619/samba

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Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction

https://github.com/alrhub/mail

공식 코드

MaIL: Improving Imitation Learning with Mamba

https://github.com/alwaysfhao/tim4rec

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TiM4Rec: An Efficient Sequential Recommendation Model Based on Time-Aware Structured State Space Duality Model

https://github.com/amai-gsu/mambev

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MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations

https://github.com/amazon-science/LC-PLM

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Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers

https://github.com/ameenali/hiddenmambaattn

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The Hidden Attention of Mamba Models

https://github.com/anasiri/bu-mamba

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Vision Mamba for Classification of Breast Ultrasound Images

https://github.com/andrasschin/SepMamba

공식 코드

SepMamba: State-space models for speaker separation using Mamba

https://github.com/andycao1125/mambadm

공식 코드

Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning

https://github.com/another-0/dmm

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DMM: Disparity-guided Multispectral Mamba for Oriented Object Detection in Remote Sensing

https://github.com/anthonyweidai/MobileViM_3D

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MobileViM: A Light-weight and Dimension-independent Vision Mamba for 3D Medical Image Analysis

https://github.com/anupsingh15/BEST-STD

공식 코드

BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term Detection

https://github.com/aopolin-lv/DecisionMamba

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Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

https://github.com/applied-machine-learning-lab/findrec

공식 코드

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation

https://github.com/arnab-api/romba

공식 코드

Locating and Editing Factual Associations in Mamba

https://github.com/ashesham/tv3s

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Exploiting Temporal State Space Sharing for Video Semantic Segmentation

https://github.com/asleepytree/freqmamba

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FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining

https://github.com/assafbk/OPRM

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Overflow Prevention Enhances Long-Context Recurrent LLMs

https://github.com/assafbk/decimamba

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DeciMamba: Exploring the Length Extrapolation Potential of Mamba

https://github.com/athms/mad-lab

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Mechanistic Design and Scaling of Hybrid Architectures

https://github.com/atik-ahamed/mambatab

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MambaTab: A Plug-and-Play Model for Learning Tabular Data

https://github.com/atik-ahamed/timemachine

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TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting

https://github.com/atlasanalyticslab/2dmamba

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2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image Classification

https://github.com/atlasanalyticslab/vim4path

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Vim4Path: Self-Supervised Vision Mamba for Histopathology Images

https://github.com/automl/is_mamba_capable_of_icl

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Is Mamba Capable of In-Context Learning?

https://github.com/automl/mamba4cast

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Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models

https://github.com/automl/unlocking_state_tracking

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Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

https://github.com/avkskvl/das-f-model

공식 코드

A Diff-Attention Aware State Space Fusion Model for Remote Sensing Classification

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