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20172026
most citedSegment Anything in Medical Images

2.8k citations

Showing 2023Show all

45 papers · 1 filter

physics.optics2023★ 2 cited

Reconfigurable quantum photonic circuits based on quantum dots

Adam McCaw, Jacob Ewaniuk, Bhavin J. Shastri +1

Quantum photonic integrated circuits, composed of linear-optical elements, offer an efficient way for encoding and processing quantum information on-chip. At their core, these circ…

quant-ph2023★ 11 cited

Further improving quantum algorithms for nonlinear differential equations via higher-order methods and rescaling

Pedro C. S. Costa, Philipp Schleich, Mauro E. S. Morales +1

The solution of large systems of nonlinear differential equations is needed for many applications in science and engineering. In this study, we present three main improvements to e…

quant-ph2023★ 78 cited

Does provable absence of barren plateaus imply classical simulability?

M. Cerezo, Martin Larocca, Diego García-Martín +9

A large amount of effort has recently been put into understanding the barren plateau phenomenon. In this perspective article, we face the increasingly loud elephant in the room and…

cs.DC2023★ 11 cited

HybridTier: an Adaptive and Lightweight CXL-Memory Tiering System

Kevin Song, Jiacheng Yang, Zixuan Wang +3

Modern workloads are demanding increasingly larger memory capacity. Compute Express Link (CXL)-based memory tiering has emerged as a promising solution for addressing this problem…

cs.LG2023★ 9 cited

Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance

Austin Cheng, Alston Lo, Santiago Miret +2

Structure determination is necessary to identify unknown organic molecules, such as those in natural products, forensic samples, the interstellar medium, and laboratory syntheses.…

cs.LG2023★ 6 cited

Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning

Jiaqi Li, Yuanhao Lai, Rui Wang +7

Continual learning aims to learn a series of tasks sequentially without forgetting the knowledge acquired from the previous ones. In this work, we propose the Hessian Aware Low-Ran…