Practicing a new habit under these four conditions can change millions and possibly billions of brain connections. The discovery of neural plasticity is a breakthrough that has significantly altered our understanding of how to change habits, increase happiness, improve health & change our genes

We have developed a search algorithm based on neural networks. Compared to our previous algorithm, the new algorithm shows relevant products up to 23% more often and up to 14% more accurately predicts the next product a user will interact with. We tell you about the other benefits in the article. Key benefits of the

We demonstrate how to code a Artificial neural network model and train and save it in JSON or H5 format which can be loaded later for any inference task. We use Keras/ TensorFlow to demonstrate this transfer learning and used Pima Indian Diabetes dataset in CSV format

From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural NetworksCai Zhou, Xiyuan Wang, Muhan ZhangRelation

Recent work has introduced attacks that extract the architecture information of deep neural networks (DNN), as this knowledge enhances an adversary's capability to conduct black-box attacks against the model. This paper presents the first in-depth security analysis of DNN fingerprinting attacks that exploit cache side-channels. First, we define the threat model for these attacks: our adversary does not need the ability to query the victim model; instead, she runs a co-located process on the host machine vic

Catastrophic forgetting, an innate issue with backpropagation learning algorithms, is a challenging problem in artificial and spiking neural network (ANN and SNN) research

ACL Anthology About Announcements Communication channels Related work Copyright Credits Volunteer Development Feedback Using Citing papers Links in the Anthology Data access All FAQs Details Anthology identifiers Names ORCID iDs DOIs Verified authors Contributions Submissions Corrections Author pages Attachments GitHub How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech Aditya Yedetore , Tal Linzen , Robert Frank , R. Thomas McCoy Correct Meta

How getML’s FastProp algorithm helps optimize your Graph Neural Network

Over the last few years the idea of “conditional computation” has been key to making neural network processing more efficient, even though much of the

Hierarchical Reasoning Model (HRM) is a novel approach using two small neural networks recursing at different frequencies. This biologically inspired method beats Large Language models (LLMs) on hard puzzle tasks such as Sudoku, Maze, and A