1 citations · 3 across the 8 of their papers we have counts for
9 papers
Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
Saksham Kiroriwal, Julius Pfrommer, Jürgen Beyerer
We study Bayesian optimization (BO) through the lens of information geometry. Pulling back the Fisher information metric through the surrogate posterior map yields a local sensitiv…
Virtual Process Dossier: A Process-Aware Data Catalogue
Lukas Kubelka, Alexander Bott, Frank Döhner +6
We propose the Virtual Process Dossier (VPD), a Knowledge Graph-based data catalogue that also captures workflow provenance. We developed VPD for multi-stage manufacturing use-case…
Joint Parameter and State-Space Bayesian Optimization: Using Process Expertise to Accelerate Manufacturing Optimization
Saksham Kiroriwal, Julius Pfrommer, Jürgen Beyerer
Bayesian optimization (BO) is a powerful method for optimizing black-box manufacturing processes, but its performance is often limited when dealing with high-dimensional multi-stag…
Higher-Order Adversarial Patches for Real-Time Object Detectors
Jens Bayer, Stefan Becker, David Münch +2
Higher-order adversarial attacks can directly be considered the result of a cat-and-mouse game -- an elaborate action involving constant pursuit, near captures, and repeated escape…
6D Pose Estimation on Point Cloud Data through Prior Knowledge Integration: A Case Study in Autonomous Disassembly
Chengzhi Wu, Hao Fu, Jan-Philipp Kaiser +5
The accurate estimation of 6D pose remains a challenging task within the computer vision domain, even when utilizing 3D point cloud data. Conversely, in the manufacturing domain, i…
A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning
Chengzhi Wu, Qianliang Huang, Kun Jin +2
Contrastive learning is an essential method in self-supervised learning. It primarily employs a multi-branch strategy to compare latent representations obtained from different bran…
SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformity
Chengzhi Wu, Yuxin Wan, Hao Fu +5
Driven by the increasing demand for accurate and efficient representation of 3D data in various domains, point cloud sampling has emerged as a pivotal research topic in 3D computer…
Rethinking Attention Module Design for Point Cloud Analysis
Chengzhi Wu, Kaige Wang, Zeyun Zhong +5
In recent years, there have been significant advancements in applying attention mechanisms to point cloud analysis. However, attention module variants featured in various research…
Bézier Curve Gaussian Processes
Ronny Hug, Stefan Becker, Wolfgang Hübner +2
Probabilistic models for sequential data are the basis for a variety of applications concerned with processing timely ordered information. The predominant approach in this domain i…