State-of-the-art backpropagation-free learning methods employ local error feedback to direct iterative optimisation via gradient descent. Here, we examine the more ...
Deep learning, a multilayered neural-network approach inspired by the brain, has revolutionized machine learning. Its success relies on backpropagation, which computes gradients of a loss function for ...
FLUX is an educational deep learning framework that reimplements the core functionality of PyTorch and TensorFlow from scratch, using only C++ and the Standard Template Library. No external ...
1 School of Information and Electronics, Beijing Institute of Technology, Beijing, China. 2 Department of Engineering and Technology, Trine University, Fort Wayne, USA. 3 Department of Information ...
This study provides a computable, direct, and mathematically rigorous approximation to the differential geometry of class manifolds for high-dimensional data, along with non-linear projections from ...
Laboratory of Light-Duty Gas-Turbine, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China University of Chinese Academy of Sciences, Beijing 100049, China ...
Recurrent neural networks (RNNs) have been proved very successful at modeling sequential data such as language or motions. However, these successes rely on the use of the backpropagation through time ...
Almost all proteins fold to their lowest free energy state, which is determined by their amino acid sequence. Computational protein design has primarily focused on finding sequences that have very low ...
"I think we should think of AI as the intellectual equivalent of a backhoe. It will be much better than us at a lot of things" Artificial intelligence is a booming industry in 2019 with lots of new ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results