Results 51 to 60 of about 286,362 (268)

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

High level excursion set geometry for non-Gaussian infinitely divisible random fields

, 2013
We consider smooth, infinitely divisible random fields $(X(t),t\in M)$, $M\subset {\mathbb{R}}^d$, with regularly varying Levy measure, and are interested in the geometric characteristics of the excursion sets \[A_u=\{t\in M:X(t)>u\}\] over high levels u.
Adler, Robert J., Samorodnitsky, Gennady, Taylor, Jonathan E.   +2 more
core   +1 more source

A Nano‐Interception Strategy for Chronic Heart Failure: Prussian Blue Nanoparticles Disrupt Fibroblast‐Immune Communication via CCL2 Sequestration

Advanced Materials, EarlyView.
A nano‐interception strategy disrupts pathogenic fibroblast–macrophage crosstalk in chronic heart failure. Scalable Prussian blue nanoparticles selectively sequester CCL2 via ultrahigh‐affinity binding, preventing CCR2+ macrophage recruitment and breaking a key fibro‐inflammatory circuit. This approach demonstrates robust efficacy in murine and porcine
Bo Chen, Gao Wei, Guowei Zeng, Haoyu Li, Rongrong Wu, Hongyu Yan, Zijie Zhou, Kai Luo, Xiaoyang Zhang, Cong Li, Longming Huang, Lingyan Cheng, Xinjie Zhang, Jinghao Zheng, Bozhong Shi, Xiaojun Cai, Xiaomin He   +16 more
wiley   +1 more source

Weakly Supervised Conditional Random Fields Model for Semantic Segmentation with Image Patches

Applied Sciences, 2020
Image semantic segmentation (ISS) is used to segment an image into regions with differently labeled semantic category. Most of the existing ISS methods are based on fully supervised learning, which requires pixel-level labeling for training the model. As
Xinying Xu, Yujing Xue, Xiaoxia Han, Zhe Zhang, Jun Xie, Jinchang Ren   +5 more
doaj   +1 more source

Discriminative word alignment with conditional random fields [PDF]

Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06, 2006
In this paper we present a novel approach for inducing word alignments from sentence aligned data. We use a Conditional Random Field (CRF), a discriminative model, which is estimated on a small supervised training set. The CRF is conditioned on both the source and target texts, and thus allows for the use of arbitrary and overlapping features over ...
Blunsom, P, Cohn, T
openaire   +2 more sources

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

On the continuity of the vector valued and set valued conditional expectations

International Journal of Mathematics and Mathematical Sciences, 1989
In this paper we study the dependence of the vector valued conditional expectation (for both single valued and set valued random variables), on the σ–field and random variable that determine it. So we prove that it is continuous for the L1(X) convergence
Nikolaos S. Papageorgiou
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Higher Order Support Vector Random Fields for Hyperspectral Image Classification

ISPRS International Journal of Geo-Information, 2018
This paper addresses the problem of contextual hyperspectral image (HSI) classification. A novel conditional random fields (CRFs) model, known as higher order support vector random fields (HSVRFs), is proposed for HSI classification.
Junli Yang, Zhiguo Jiang, Shuang Hao, Haopeng Zhang   +3 more
doaj   +1 more source