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19942025
most citedA Comparative Study on Transformer vs RNN in Speech Applications

788 citations

Showing 2024Show all

12 papers · 1 filter

cs.CV2024★ 9 cited

SIRA: Scalable Inter-frame Relation and Association for Radar Perception

Ryoma Yataka, Pu Perry Wang, Petros Boufounos +1

Conventional radar feature extraction faces limitations due to low spatial resolution, noise, multipath reflection, the presence of ghost targets, and motion blur. Such limitations…

quant-ph2024★ 4 cited

Quantum state estimation of multi-partite single photon path entanglement via local measurements

Hikaru Shimizu, Joe Yoshimoto, Kazufumi Tanji +5

Multipartite entanglement plays a critical role in various applications of quantum internet. In these applications, the entanglement is usually shared by the distant parties. Exper…

cs.CV2024

Genetic Information Analysis of Age-Related Macular Degeneration Fellow Eye Using Multi-Modal Selective ViT

Yoichi Furukawa, Satoshi Kamiya, Yoichi Sakurada +2

In recent years, there has been significant development in the analysis of medical data using machine learning. It is believed that the onset of Age-related Macular Degeneration (A…

physics.space-ph2024★ 6 cited

Autonomous Station Keeping of Satellites in Areostationary Mars Orbit: A Predictive Control Approach

Robert D. Halverson, Avishai Weiss, Gabriel Lundin +1

The continued exploration of Mars will require a greater number of in-space assets to aid interplanetary communications. Future missions to the surface of Mars may be augmented wit…

math.OC2024★ 1 cited

Constructing Tight Quadratic Relaxations for Global Optimization: II. Underestimating Difference-of-Convex (D.C.) Functions

William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1

Recent advances in the efficiency and robustness of algorithms solving convex quadratically constrained quadratic programming (QCQP) problems motivate developing techniques for cre…

math.OC2024★ 1 cited

Constructing Tight Quadratic Relaxations for Global Optimization: I. Outer-Approximating Twice-Differentiable Convex Functions

William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1

When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency a…