Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, ...

Lab-grown “reductionist replicas” of the human brain are helping scientists understand fetal development and cognitive disorders, including autism. But ethical questions loom. Brain organoids, which ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Abstract: Adversarial examples have become a critical focus in ensuring the security and robustness of deep learning (DL) systems. In this paper, we introduce an innovative approach for generating ...

We are excited to share our first big milestone in solving a grand challenge that has hampered the predictive power of computational chemistry, biochemistry, and materials science for decades. By ...

Abstract: To address the challenges of blended teaching, this study focuses on deep learning, taking “Early Reading and Guidance” as an example, to conduct research on blended teaching practice. First ...

This book is aimed to provide an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the ...