GitHub

batch-gradient-descent

From-scratch NumPy implementations of Perceptron and Multi-Layer Perceptron (MLP) for deep learning coursework, with experiments on Gaussian datasets, make_moons, and batch size analysis for BGD/SGD.
C&EN

Multivariable System Prediction Based on TCN-LSTM Networks with Self-Attention Mechanism ...

Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China School of Information and Control ...
GitHub

The History of Neural Networks Part 2: Rosenblatt's Perceptron

In 1957, Rosenblatt published pioneering work on the first machine learning algorithm for artificial neurons, known as the perceptron. He helped revolutionize the field of artificial intelligence ...
Frontiers

Reservoir based spiking models for univariate Time Series Classification

A variety of advanced machine learning and deep learning algorithms achieve state-of-the-art performance on various temporal processing tasks. However, these methods are heavily energy ...
Frontiers

CPD-Structured Multivariate Polynomial Optimization

We introduce the Tensor-Based Multivariate Optimization (TeMPO) framework for use in nonlinear optimization problems commonly encountered in signal processing, machine learning, and artificial ...
ascopubs.org

Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on ...

HealthTree Cure Hub: A Patient-Derived, Patient-Driven Clinical Cancer Information Platform Used to Overcome Hurdles and Accelerate Research in Multiple Myeloma Adversarial images represent a ...