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Data Compression

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Showing 1–50 of 459 papers

TitleStatusHype
Uncover Treasures in DCT: Advancing JPEG Quality Enhancement by Exploiting Latent Correlations—0
GratNet: A Photorealistic Neural Shader for Diffractive Surfaces—0
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical dataCode0
Kernel k-Medoids as General Vector Quantization—0
Fourier-Modulated Implicit Neural Representation for Multispectral Satellite Image Compression—0
Stationary MMD Points for CubatureCode0
Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables—0
MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language ModelsCode1
Efficient compression of neural networks and datasetsCode0
Learning novel representations of variable sources from multi-modal Gaia data via autoencoders—0
Combining Progressive Image Compression and Random Access in DNA Data Storage—0
DD-Ranking: Rethinking the Evaluation of Dataset DistillationCode2
Is Compression Really Linear with Code Intelligence?—0
Clustering-based Low-Rank Matrix Approximation: An Adaptive Theoretical Analysis with Application to Data Compression—0
Towards Scalable IoT Deployment for Visual Anomaly Detection via Efficient Compression—0
Event-based Neural Spike Detection Using Spiking Neural Networks for Neuromorphic iBMI Systems—0
ReplayCAD: Generative Diffusion Replay for Continual Anomaly DetectionCode2
3D Gaussian Splatting Data Compression with Mixture of Priors—0
HybridGS: High-Efficiency Gaussian Splatting Data Compression using Dual-Channel Sparse Representation and Point Cloud EncoderCode1
Convolutional Autoencoders for Data Compression and Anomaly Detection in Small Satellite Technologies—0
Quantum Autoencoder for Multivariate Time Series Anomaly Detection—0
FPGA-Based Neural Network Accelerators for Space Applications: A Survey—0
DeepSelective: Feature Gating and Representation Matching for Interpretable Clinical Prediction—0
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations—0
VAE-based Feature Disentanglement for Data Augmentation and Compression in Generalized GNSS Interference Classification—0
Representing Flow Fields with Divergence-Free Kernels for Reconstruction—0
An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU functionCode0
Nonlinear Multiple Response Regression and Learning of Latent Spaces—0
UniPCGC: Towards Practical Point Cloud Geometry Compression via an Efficient Unified ApproachCode2
SeisRDT: Latent Diffusion Model Based On Representation Learning For Seismic Data Interpolation And Reconstruction—0
Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression—0
Edge-Fog Computing-Enabled EEG Data Compression via Asymmetrical Variational Discrete Cosine Transform Network—0
Lossy Neural Compression for Geospatial Analytics: A Review—0
Quantum autoencoders for image classification—0
Guaranteed Conditional Diffusion: 3D Block-based Models for Scientific Data Compression—0
Solving Optimal Power Flow on a Data-Budget: Feature Selection on Smart Meter Data—0
Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels—0
Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions—0
Efficient Bearing Sensor Data Compression via an Asymmetrical Autoencoder with a Lifting Wavelet Transform Layer—0
Mathematical model of parameters relevance in adaptive level-crossing sampling for electrocardiogram signals—0
Artificial Intelligence in Creative Industries: Advances Prior to 2025—0
Remote Inference over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector QuantizationCode0
Foundation Model for Lossy Compression of Spatiotemporal Scientific Data—0
L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text CompressionCode1
Quantum Implicit Neural Compression—0
Learned Data Compression: Challenges and Opportunities for the Future—0
Solving High-dimensional Inverse Problems Using Amortized Likelihood-free Inference with Noisy and Incomplete Data—0
Multi-Scale Node Embeddings for Graph Modeling and Generation—0
Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance SamplingCode0
Construction of generalized samplets in Banach spaces—0
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