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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/0x1DA9430/Decision-Transformer-vs-Decision-Mamba

공식 코드

Decision Transformer vs. Decision Mamba: Analysing the Complexity of Sequential Decision Making in Atari Games

https://github.com/12138-chr/mtair

공식 코드

Multi-dimensional Visual Prompt Enhanced Image Restoration via Mamba-Transformer Aggregation

https://github.com/2760613195/km_unet

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KM-UNet KAN Mamba UNet for medical image segmentation

https://github.com/294coder/efficient-mif

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A Novel State Space Model with Local Enhancement and State Sharing for Image Fusion

https://github.com/924973292/mambapro

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MambaPro: Multi-Modal Object Re-Identification with Mamba Aggregation and Synergistic Prompt

https://github.com/983632847/awesome-multimodal-object-tracking

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MambaTrack: Exploiting Dual-Enhancement for Night UAV Tracking

https://github.com/AI-in-Cardiovascular-Medicine/nnUZoo

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From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image Segmentation

https://github.com/ALRhub/X_IL

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X-IL: Exploring the Design Space of Imitation Learning Policies

https://github.com/Alena-Xinran/MaTAV

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Mamba-Enhanced Text-Audio-Video Alignment Network for Emotion Recognition in Conversations

https://github.com/Amshaker/GroupMamba

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GroupMamba: Efficient Group-Based Visual State Space Model

https://github.com/AndssY/DeMa

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Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?

https://github.com/Applied-Machine-Learning-Lab/SIMGA

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SIGMA: Selective Gated Mamba for Sequential Recommendation

https://github.com/Arhosseini77/SUM

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SUM: Saliency Unification through Mamba for Visual Attention Modeling

https://github.com/Atik-Ahamed/TSCMamba

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TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification

https://github.com/Audio-WestlakeU/UMA-ASR

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Mamba for Streaming ASR Combined with Unimodal Aggregation

https://github.com/AutoLab-SAI-SJTU/MambaFusion

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MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection

https://github.com/Axect/Neural_Hamilton

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Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?

https://github.com/Binwen6/CS182_PROJECT_2025

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Probing In-Context Learning: Impact of Task Complexity and Model Architecture on Generalization and Efficiency

https://github.com/Bond1995/Markov-Mamba

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From Markov to Laplace: How Mamba In-Context Learns Markov Chains

https://github.com/CV4RA/MambaPlace

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MambaPlace:Text-to-Point-Cloud Cross-Modal Place Recognition with Attention Mamba Mechanisms

https://github.com/Cedarch/M3Net

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M3Net: Multimodal Multi-task Learning for 3D Detection, Segmentation, and Occupancy Prediction in Autonomous Driving

https://github.com/Chernobyllight/SaMam

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SaMam: Style-aware State Space Model for Arbitrary Image Style Transfer

https://github.com/CompVis/zigma

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ZigMa: A DiT-style Zigzag Mamba Diffusion Model

https://github.com/Cranial-XIX/longhorn

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Longhorn: State Space Models are Amortized Online Learners

https://github.com/Devin-Egber/UV-Mamba

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UV-Mamba: A DCN-Enhanced State Space Model for Urban Village Boundary Identification in High-Resolution Remote Sensing Images

https://github.com/EleutherAI/rnngineering

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Does Transformer Interpretability Transfer to RNNs?

https://github.com/ErgastiAlex/U-Shape-Mamba

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U-Shape Mamba: State Space Model for faster diffusion

https://github.com/FarnoushRJ/MambaLRP

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MambaLRP: Explaining Selective State Space Sequence Models

https://github.com/HazyResearch/prefix-linear-attention

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Just read twice: closing the recall gap for recurrent language models

https://github.com/HenryZhou19/E-ViM3

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Mamba-3D as Masked Autoencoders for Accurate and Data-Efficient Analysis of Medical Ultrasound Videos

https://github.com/HiLab-git/GLFC

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GLFC: Unified Global-Local Feature and Contrast Learning with Mamba-Enhanced UNet for Synthetic CT Generation from CBCT

https://github.com/Itamarzimm/UnifiedImplicitAttnRepr

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Explaining Modern Gated-Linear RNNs via a Unified Implicit Attention Formulation

https://github.com/Jiaxin-Ye/DepMamba

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DepMamba: Progressive Fusion Mamba for Multimodal Depression Detection

https://github.com/Joker-ZXR/TSSC-Net

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A Diffusion-Driven Temporal Super-Resolution and Spatial Consistency Enhancement Framework for 4D MRI imaging

https://github.com/KatherLab/COBRA

공식 코드

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning

https://github.com/KyanChen/RSMamba

공식 코드

RSMamba: Remote Sensing Image Classification with State Space Model

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