Complete PyTorch reproduction of Google's TITANS, MIRAS, and NL neural memory papers. 52 tests, 87% coverage, Docker support.
Official implementation of "RefP2C: Reflective Paper-to-Code Development Enabled by Fine-Grained Verification".
Research-reproduction Agent: PDF → factor code → backtest → Red Team → reproducibility score. Part of the alpha-kit stack.
implementing Quantum Bayes Classifiers (QBCs) for image classification tasks using MNIST and Fashion-MNIST datasets, based on the research by Ming-Ming Wang and Xiao-Ying Zhang. The project includes Naïve QBC, SPODE-QBC, TAN-QBC, and Symmetric-QBC, simulated on MindQuantum.
Contains files for my reproduction of experiments from Harnik et al.'s "To Zip or not to Zip" (2013) paper.
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