Autoscience builds automated research lab for machine learning models with $14M

Artificial intelligence startup Autoscience Institute has launched with $14 million in seed funding to automate research into ...
AOL

Understanding The Functions On Your Smart LG Washing Machine

When considering the most popular washer and dryer brands in the USA, LG consistently ranks at the top. It's no surprise, since they are widely recognized for their reliability and user-friendly ...
eLife

An interpretable neural network unveils higher-order epistasis in large protein sequence-function relationships

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...
IEEE

Deep Learning Based Intrusion Detection System using Gated Recurrent Neural Network with Sigmoid Activation Function

Abstract: In recent years, Intrusion Detection System (IDS) significant progress has been made in the area of computer networks and the internet. This brings up significant security concerns. Since ...
Medical Xpress

Unveiling schizophrenia's neural and mental signatures with machine learning

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.
Frontiers

Enhancing structure-based virtual screening of MDM2–p53 inhibitors: a benchmark of machine learning vs. traditional docking scoring functions

The interaction between p53 and MDM2 represents a key therapeutic target in several cancers where MDM2 overexpression suppresses p53 activity. Despite extensive research, the discovery of potent and ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...
Scientific Research Publishing

Pennington, J., Schoenholz, S.S. and Ganguli, S. (2017) Resurrecting the Sigmoid in Deep Learning Through Dynamical Isometry: Theory and Practice. Advances in Neural ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Frontiers

Factors affecting subjective cognitive decline: an automated machine learning approach

A retrospective cohort study collected clinical psychological factor data from the “Active Health” screening app under the National Key R&D Program. The final dataset included 598 samples, with an SCD ...
ascopubs.org

Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy

Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor ...
Scientific Research Publishing

Asaad, R.R. and Ali, R.I. (2019) Back Propagation Neural Network (BPNN) and Sigmoid Activation Function in Multi-Layer Networks. Academic Journal of Nawroz University, 8, 216-221.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
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 Tropical Storm ...