Leveraging network motifs to improve artificial neural networks

Research project analyzing stability and robustness of deep learning optimizers (SGD, Adam, SAM) under label noise and precision constraints.

Detect numerical instability in ML applications using learned invariants (Soft Assertions) without modifying model logic. ACM FSE 2025.

This course is part of the USC Graduate Biostatistics Program and is designed for second-year and beyond students interested in designing and implementing computational inferential tools for research.

A hands‑on, first‑principles guide to fitting logistic regression via the Iteratively Reweighted Least Squares (IRLS) algorithm complete with mathematical derivations, R code from scratch, and a real‑world S&P data case study to bring your statistical modeling skills to the next level.

A lightweight C++ tool that prices European call and put options using the Black–Scholes formula, computes all key Greeks (Δ, Γ, Θ, Vega, Rho), and lets you run quick ATM/ITM/OTM scenario checks—all via a simple command‑line interface.

StableStockPredictor is a robust deep learning model for predicting S&P 500 stock prices, built with TensorFlow and Keras. It leverages LSTM networks with gradient clipping, robust scaling, and stable feature engineering (e.g., RSI, moving averages, volatility) to ensure reliable performance in volatile markets.

This MATLAB function efficiently computes the inverse of a square matrix using LU factorization. By decomposing the matrix into lower and upper triangular matrices, the function solves for the inverse with improved numerical stability.

17 specialized AI agents for comprehensive ML pipeline bug detection. Works with GitHub Copilot and Claude Code.

R package and replication code for the article “Numerical stability enhancements in beta autoregressive moving average model estimation” by Cribari-Neto, F., Costa, E., and Fonseca, R. V., published in the Brazilian Journal of Probability and Statistics (2025). DOI: 10.1214/25-BJPS645.

Compute the arithmetic mean along one or more ndarray dimensions using a two-pass error correction algorithm.