This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

Understanding the effects of data parallelism and sparsity on neural network training

Neural Network Training Fingerprint (NNTF) is a visualization approach to analyze the training process of any neural network performing classification.

Conjunto de ferramentas para lidar com treinamentos de redes neurais artificiais

Neural network for recognizing handwritten numbers

🧠 Automated neural network ablation studies using LLM agents and LangGraph. Systematically remove components, test performance, and gain insights into architecture importance through an intelligent multi-agent workflow.

This notebook provides source code of my work for my Master's Thesis.

Modifies a neural network's hyperparameters, activation functions, cost functions, and regularization methods to improve training performance and generalization.

An Open Source Machine Learning Framework for Everyone

Real-time Object Detection and Neural Network Training Visualization

Modifies a neural network's hyperparameters, activation functions, cost functions, and regularization methods to improve training performance and generalization.

Simple implementation of a 3 layer MLP network using numpy.

This repository documents the process of finding the optimal learning rate for deep neural networks

A memory-efficient, gradient-free zeroth-order (derivative-free) optimizer designed to solve the "Curse of Dimensionality" in Black-Box optimization and memory-constrained Machine Learning. It provides an O(log D) gradient estimation approach that can successfully train Neural Networks without ever calculating analytical derivatives or Backprop