Quantum-Enhanced Inference of Conditional Future Probabilities with Reduced Memory Cost

arXiv:2610.10756 · quant-ph · Submitted 2026-10-07 · Read on arXiv

quant-ph

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Quantum Amplitude Estimation — 7× in this paper
• Quantization — 6× in this paper · explained in 12 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Quantum Circuits — 4× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Ancilla Qubits — 2× in this paper · explained in 1 episode
• Clustering — 2× in this paper · explained in 2 episodes
• Linear Increment Schedule — 2× in this paper
• Maximum Likelihood Amplitude Estimation — 2× in this paper
• Quantum Fidelity Divergence Rate — 2× in this paper
• Sample Complexity — 2× in this paper · explained in 15 episodes
• Systematic Bias — 2× in this paper · explained in 3 episodes
• Approximate Counting — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• By Singular Value Decomposition — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Exponential Increment Schedule — 1× in this paper
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
• Temporal Correlations — 1× in this paper · explained in 2 episodes

Sources

• A Survey of Model Compression and Acceleration for Deep Neural Networks
• Transformers represent belief state geometry in their residual stream
• Towards the Limit of Network Quantization
• Compressing Deep Convolutional Networks using Vector Quantization

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