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Information Theory

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Information Theory

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Research Frontiers in Source Coding and Compression

Develops optimal algorithms for compressing information sources while preserving essential data characteristics and minimizing bit rates.

Lossy Compression at the Edge of Perception
Semantic Compression Beyond Shannon Entropy
Adaptive Coding in Non-Stationary Information Streams
Neural Network Compression Through Information Bottlenecks
Context-Aware Quantization in High-Dimensional Data
Rate-Distortion Tradeoffs in Multimodal Sources
Distributed Source Coding for Correlated Data
Compression Under Adversarial and Noisy Channels
Lossless Compression of Structured Symbolic Data
Quantum Information Compression and State Encoding

All Information Theory PhD categories