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State Space Models

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Showing 151–200 of 923 papers

TitleStatusHype
Implicit Language Models are RNNs: Balancing Parallelization and ExpressivityCode1
XAMBA: Enabling Efficient State Space Models on Resource-Constrained Neural Processing UnitsCode0
Adversarial Transform Particle FiltersCode0
CMamba: Learned Image Compression with State Space Models—0
The α-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and PerformanceCode0
Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory—0
Sequence models for continuous cell cycle stage prediction from brightfield images—0
Layer by Layer: Uncovering Hidden Representations in Language Models—0
Multilingual State Space Models for Structured Question Answering in Indic LanguagesCode0
Secure Data Reconstruction: A Direct Data-Driven Approach—0
SatMamba: Development of Foundation Models for Remote Sensing Imagery Using State Space ModelsCode0
Mamba-Shedder: Post-Transformer Compression for Efficient Selective Structured State Space Models—0
Application of Structured State Space Models to High energy physics with locality-sensitive hashing—0
Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware SparsityCode2
MambaTron: Efficient Cross-Modal Point Cloud Enhancement using Aggregate Selective State Space Modeling—0
On the locality bias and results in the Long Range Arena—0
State Space Models for Extractive Summarization in Low Resource Scenarios—0
QMamba: Post-Training Quantization for Vision State Space Models—0
Contrast: A Hybrid Architecture of Transformers and State Space Models for Low-Level Vision—0
GRAMA: Adaptive Graph Autoregressive Moving Average Models—0
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions—0
Parallel Sequence Modeling via Generalized Spatial Propagation Network—0
Test-time regression: a unifying framework for designing sequence models with associative memory—0
On the dimension of pullback attractors in recurrent neural networks—0
SeRpEnt: Selective Resampling for Expressive State Space Models—0
WSSM: Geographic-enhanced hierarchical state-space model for global station weather forecast—0
Finite Sample Analysis of Subspace Identification Methods—0
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI ReconstructionCode1
Gaussian Integral based Bayesian Smoother—0
Meta-Learning for Physically-Constrained Neural System Identification—0
Element-wise Attention Is All You Need—0
TREAD: Token Routing for Efficient Architecture-agnostic Diffusion TrainingCode2
H-MBA: Hierarchical MamBa Adaptation for Multi-Modal Video Understanding in Autonomous Driving—0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models—0
KM-UNet KAN Mamba UNet for medical image segmentationCode1
On Symmetries in Analytic Input-Output Systems—0
A Separable Self-attention Inspired by the State Space Model for Computer VisionCode0
Merging Context Clustering with Visual State Space Models for Medical Image SegmentationCode2
CryptoMamba: Leveraging State Space Models for Accurate Bitcoin Price PredictionCode3
ACL: Activating Capability of Linear Attention for Image Restoration—0
Mamba4D: Efficient 4D Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space ModelsCode1
Spectral Informed Mamba for Robust Point Cloud Processing—0
Spectral State Space Model for Rotation-Invariant Visual Representation Learning—0
Event-based Video Super-Resolution via State Space Models—0
DefMamba: Deformable Visual State Space Model—0
Adjoint sharding for very long context training of state space models—0
GDSR: Global-Detail Integration through Dual-Branch Network with Wavelet Losses for Remote Sensing Image Super-Resolution—0
Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothingCode1
Fitting Dynamically Misspecified Models: An Optimal Transportation Approach—0
IMSSA: Deploying modern state-space models on memristive in-memory compute hardware—0
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