Google's new multi-vector retrieval algorithm (MUVERA) improves search speed and performs better on complex queries.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Therefore, we tested the potential of new deep learning-based image-matching algorithms for deriving glacier surface velocities across the ablation area of a glacier with strong spatial variability in ...

In numerous application areas, high-dimensional nonlinear filtering is still a challenging problem. The introduction of deep learning and neural networks has improved the efficiency of classical ...

Deep learning, particularly 3D U-Net architectures, has revolutionised medical image analysis by leveraging volumetric data to capture spatial context, enhancing segmentation accuracy. This paper ...

Communication overhead is a significant challenge in distributed deep learning (DDL) training, often hindering efficiency. While existing solutions like gradient compression, compute/communication ...

Keywords: pancreatic tumor segmentation, cascaded algorithm, deep learning, non-local localization module, focusing module Citation: Qiu D, Ju J, Ren S, Zhang T, Tu H, Tan X and Xie F (2024) A deep ...

Recently, Shaila Niazi, a third-year doctoral student in Çamsari’s lab, achieved a significant breakthrough in that effort, becoming the first to use probabilistic hardware to train a deep generative ...

Professor Zhou's latest project, titled "Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models," attempts to solve the overshoot issue. He explains, "The Adan optimizer can ...

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...