Relational Compression: A Framework for Relational Fidelity in Constrained Representations
cs.LG, cs.IT, math.IT
Submitted: 2026-09-25
Updated: 2026-09-25
Code: https://github.com/yaniv-shulman/relational-compression
Terminology
Sources
- TUDataset: A collection of benchmark datasets for learning with graphs
- GAP: Generalizable Approximate Graph Partitioning Framework
- BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers
- DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization
- Exact Backpropagation in Binary Weighted Networks with Group Weight Transformations
- Variable Rate Image Compression with Recurrent Neural Networks
- Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation
- Image and Video Tokenization with Binary Spherical Quantization
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