We develop an optimal quantization approach for numerically solving nonlinear filtering problems associated with discrete-time or continuous-time state processes and discrete-time observations. Two ...

But it got us just far enough to ask ourselves how much noise is required in the system for oversampling to help in reducing quantization noise.

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy.

We discuss a framework for strict deformation quantization (in the sense of Rieffel) based on a GNS-type construction. These methods are applied then to prove that the quantum SU (N) groups produce a ...

After analyzing the DeepSeek-R1 architecture, unsloth performed 'dynamic quantization,' which quantizes each part of the model at a different compression rate.

Google's new Quantization Aware Training API supports the development of smaller, faster models that don't compromise on accuracy.