Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable Bayesian inference in deep learning models to quantify principled uncertainty estimates in ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

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 ...

Patients with NSCLC completed the PROMIS-57 PRO quality-of-life measure and wore a Fitbit to monitor patient-generated health data from ST initiation through day 60. Demographic and clinical data were ...

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

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

ABSTRACT: The present study aimed to examine the impact of emotion regulation on depression symptoms, with a particular focus on the mediating roles of social anxiety and loneliness among Chinese ...

Anomaly response in aerospace systems increasingly relies on multi-model analysis in digital twins to replicate the system’s behaviors and inform decisions. However, computer model calibration methods ...

This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full text component.