Search Results for author: Yan Yu

Found 8 papers, 2 papers with code

Three-dimensional Reconstruction of the Lumbar Spine with Submillimeter Accuracy Using Biplanar X-ray Images

no code implementations18 Mar 2025 Wanxin Yu, Zhemin Zhu, Cong Wang, Yihang Bao, Chunjie Xia, Rongshan Cheng, Yan Yu, Tsung-Yuan Tsai

This study developed and validated a fully automated method for high-accuracy 3D reconstruction of the lumbar spine from biplanar X-ray images.

3D Reconstruction

Model Evolution Framework with Genetic Algorithm for Multi-Task Reinforcement Learning

no code implementations19 Feb 2025 Yan Yu, Wengang Zhou, Yaodong Yang, Wanxuan Lu, Yingyan Hou, Houqiang Li

To this end, we propose a Model Evolution framework with Genetic Algorithm (MEGA), which enables the model to evolve during training according to the difficulty of the tasks.

SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC

1 code implementation23 Dec 2024 Yue Deng, Yan Yu, Weiyu Ma, ZiRui Wang, Wenhui Zhu, Jian Zhao, Yin Zhang

SMAC-HARD supports customizable opponent strategies, randomization of adversarial policies, and interfaces for MARL self-play, enabling agents to generalize to varying opponent behaviors and improve model stability.

Benchmarking SMAC+ +1

DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models

no code implementations9 Oct 2024 Yiming Huang, Jianwen Luo, Yan Yu, Yitong Zhang, Fangyu Lei, Yifan Wei, Shizhu He, Lifu Huang, Xiao Liu, Jun Zhao, Kang Liu

We introduce DA-Code, a code generation benchmark specifically designed to assess LLMs on agent-based data science tasks.

Code Generation

Skipped Feature Pyramid Network with Grid Anchor for Object Detection

no code implementations22 Oct 2023 Li Pengfei, Wei Wei, Yan Yu, Zhu Rong, Zhou Liguo

In our method, the lower-level feature only connects with the feature at the highest level, making it more reasonable that each level is responsible for detecting objects with fixed scales.

Object object-detection +1

Image Compressed Sensing with Multi-scale Dilated Convolutional Neural Network

1 code implementation28 Sep 2022 Zhifeng Wang, Zhenghui Wang, Chunyan Zeng, Yan Yu, Xiangkui Wan

During the measurement period, we directly obtain all measurements from a trained measurement network, which employs fully convolutional structures and is jointly trained with the reconstruction network from the input image.

compressed sensing Image Compressed Sensing +2

Abs-CAM: A Gradient Optimization Interpretable Approach for Explanation of Convolutional Neural Networks

no code implementations8 Jul 2022 Chunyan Zeng, Kang Yan, Zhifeng Wang, Yan Yu, Shiyan Xia, Nan Zhao

However, when this method uses backpropagation to obtain gradients, it will cause noise in the saliency map, and even locate features that are irrelevant to decisions.

Obstacles to Constructing de Sitter Space in String Theory

no code implementations27 Aug 2020 Michael Dine, Jamie A. P. Law-Smith, Shijun Sun, Duncan Wood, Yan Yu

While arguably there have been some successes, this has proven challenging, leading to the de Sitter swampland conjecture: quantum theories of gravity do not admit stable or metastable de Sitter space.

High Energy Physics - Theory High Energy Physics - Phenomenology

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