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State Space Models

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

https://github.com/facebookresearch/length-and-compositional-generalization

공식 코드

On Provable Length and Compositional Generalization

https://github.com/facebookresearch/mega

공식 코드

Mega: Moving Average Equipped Gated Attention

https://github.com/feizc/dis

공식 코드

Scalable Diffusion Models with State Space Backbone

https://github.com/fenghetan9/mambamim

공식 코드

MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation

https://github.com/fla-org/flash-linear-attention

공식 코드

Parallelizing Linear Transformers with the Delta Rule over Sequence Length

https://github.com/flbbb/locost-summarization

공식 코드

LOCOST: State-Space Models for Long Document Abstractive Summarization

https://github.com/forgi86/lru-reduction

공식 코드

Model order reduction of deep structured state-space models: A system-theoretic approach

https://github.com/forgi86/sysid-neural-continuous

공식 코드

Continuous-time system identification with neural networks: Model structures and fitting criteria

https://github.com/forgi86/sysid-neural-estimator

공식 코드

Learning neural state-space models: do we need a state estimator?

https://github.com/forgi86/sysid-neural-unc

공식 코드

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

https://github.com/furiocolombo/mamba-foley

공식 코드

MambaFoley: Foley Sound Generation using Selective State-Space Models

https://github.com/furiosa-ai/ssm-peft

공식 코드

Parameter-Efficient Fine-Tuning of State Space Models

https://github.com/furiosa-ai/ssm-state-tuning

공식 코드

State-offset Tuning: State-based Parameter-Efficient Fine-Tuning for State Space Models

https://github.com/gatech-eic/longmamba

공식 코드

LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement

https://github.com/gd-vae/gd-vae

공식 코드

GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions

https://github.com/gerbenbeintema/ct-subnet

공식 코드

Continuous-time identification of dynamic state-space models by deep subspace encoding

https://github.com/gerbenbeintema/metass-code-repo

공식 코드

Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems

https://github.com/gerdm/weighted-likelihood-filter

공식 코드

Outlier-robust Kalman Filtering through Generalised Bayes

https://github.com/gndlwch2w/msvm-unet

공식 코드

MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image Segmentation

https://github.com/goombalab/hydra

공식 코드

Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers

https://github.com/gpantaz/vl_mamba

공식 코드

Shaking Up VLMs: Comparing Transformers and Structured State Space Models for Vision & Language Modeling

https://github.com/graph-com/gssc

공식 코드

What Can We Learn from State Space Models for Machine Learning on Graphs?

https://github.com/graphmamba/gmn

공식 코드

Graph Mamba: Towards Learning on Graphs with State Space Models

https://github.com/gwenzhang/voxel-mamba

공식 코드

Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection

https://github.com/hainuo-wang/modem

공식 코드

MODEM: A Morton-Order Degradation Estimation Mechanism for Adverse Weather Image Recovery

https://github.com/hanyas/wasserstein-flow-filter

공식 코드

Variational Gaussian filtering via Wasserstein gradient flows

https://github.com/hashmatshadab/mambarobustness

공식 코드

Towards Evaluating the Robustness of Visual State Space Models

https://github.com/hazyresearch/h3

공식 코드

Hungry Hungry Hippos: Towards Language Modeling with State Space Models

https://github.com/hazyresearch/safari

공식 코드

Simple Hardware-Efficient Long Convolutions for Sequence Modeling

https://github.com/hazyresearch/spacetime

공식 코드

Effectively Modeling Time Series with Simple Discrete State Spaces

https://github.com/hazyresearch/state-spaces

공식 코드

It's Raw! Audio Generation with State-Space Models

https://github.com/hcarlsso/array-in

공식 코드

Inertial Navigation Using an Inertial Sensor Array

https://github.com/hoqolo/sdstrack

공식 코드

Awesome Multi-modal Object Tracking

https://github.com/humml-lab/GTF-ConvSSM

공식 코드

A scalable generative model for dynamical system reconstruction from neuroimaging data

https://github.com/hunto/localmamba

공식 코드

LocalMamba: Visual State Space Model with Windowed Selective Scan

https://github.com/hustvl/mmmamba

공식 코드

Multimodal Mamba: Decoder-only Multimodal State Space Model via Quadratic to Linear Distillation

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