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Data Compression

Papers

Showing 101125 of 459 papers

TitleStatusHype
Guaranteed Conditional Diffusion: 3D Block-based Models for Scientific Data Compression0
Solving Optimal Power Flow on a Data-Budget: Feature Selection on Smart Meter Data0
Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels0
Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions0
Efficient Bearing Sensor Data Compression via an Asymmetrical Autoencoder with a Lifting Wavelet Transform Layer0
Mathematical model of parameters relevance in adaptive level-crossing sampling for electrocardiogram signals0
Artificial Intelligence in Creative Industries: Advances Prior to 20250
Remote Inference over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector QuantizationCode0
Foundation Model for Lossy Compression of Spatiotemporal Scientific Data0
Quantum Implicit Neural Compression0
Learned Data Compression: Challenges and Opportunities for the Future0
Multi-Scale Node Embeddings for Graph Modeling and Generation0
Solving High-dimensional Inverse Problems Using Amortized Likelihood-free Inference with Noisy and Incomplete Data0
Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance SamplingCode0
Construction of generalized samplets in Banach spaces0
AIDetx: a compression-based method for identification of machine-learning generated textCode0
HEMGS: A Hybrid Entropy Model for 3D Gaussian Splatting Data Compression0
TransCompressor: LLM-Powered Multimodal Data Compression for Smart Transportation0
Variable Rate Neural Compression for Sparse Detector DataCode0
Enabling DBSCAN for Very Large-Scale High-Dimensional Spaces0
BVI-CR: A Multi-View Human Dataset for Volumetric Video CompressionCode0
Towards efficient compression and communication for prototype-based decentralized learning0
Rendering-Oriented 3D Point Cloud Attribute Compression using Sparse Tensor-based Transformer0
HiHa: Introducing Hierarchical Harmonic Decomposition to Implicit Neural Compression for Atmospheric Data0
A method based on Generative Adversarial Networks for disentangling physical and chemical properties of stars in astronomical spectra0
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