This paper presents a novel adaptive learning-rate backpropagation neural network (ALR-BPNN) algorithm based on the minimization of mean-square deviation (MSD) to implement a fast convergence rate and ...

Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these models to their ...

eLife Assessment This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be ...

Quantum computers still face a major hurdle on their pathway to practical use cases: their limited ability to correct the ...

The company says it has cracked the code for error correction and is building a modular machine in New York state.

Why repetition codes matter The focus on repetition codes isn't arbitrary. While other quantum error-correcting codes, like surface codes, have only achieved small distances and relatively high ...

Alignment and sequencing errors are a major concern in molecular evolution, and this valuable study represents a welcome improvement for genome-wide scans of positive selection. This new method seems ...

Scientists have developed an exact approach to a key quantum error correction problem once believed to be unsolvable, and have shown that what appeared to be hardware ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, molecules, and materials.