GitHub

JAX à la Stan

We introduce a methodology for coding Bayesian statistical models in Python with JAX that follows the design pattern of the Stan probabilistic programming language. This allows a direct, line-by-line ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python As shutdown ...
C&EN

Integrated Fault Tree Analysis and Bayesian Network for Fire Risk Assessment in University Laboratories

The rapid expansion of higher education has introduced new safety challenges in university laboratories, where fire incidents now represent a critical threat to campus safety. In this paper, we ...
ascopubs.org

Using Bayesian Networks to Predict Urgent Care Visits in Patients Receiving Systemic Therapy for Non–Small Cell Lung Cancer

Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial Patients with NSCLC completed ...
GitHub

SandyGCabanes/Anonymized-Survey-Data-Modeling-with-Bayesian-Networks-in-Python

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...
IEEE

Learning Bayesian Networks Under Local Differential Privacy

Abstract: Bayesian networks are widely used for causal discovery and probabilistic modeling across diverse domains including healthcare, multi-dimensional data analysis, environmental modeling, and ...