⚛️ Physics & Scientific Computing¶

📹 ICCV2025 · 2 paper notes

JPEG Processing Neural Operator for Backward-Compatible Coding: This paper proposes JPNeO, a next-generation codec that is fully backward-compatible with the JPEG format. By introducing neural operators at both the encoding stage (JENO) and decoding stage (JDNO), along with a trainable quantization matrix, JPNeO significantly improves JPEG reconstruction quality—particularly for chroma components—while maintaining low memory footprint and parameter count.
ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers: This paper proposes ResQ — the first framework to natively implement residual neural networks (ResNets) on analog Rydberg atom quantum computers by exploiting continuous-time Hamiltonian evolution, encoding input features and trainable parameters via piecewise parameterized laser pulses, achieving an average 50% improvement over classical models of equivalent scale on MNIST, FashionMNIST, and medical dataset classification tasks.