Conveners
Plenary: Short Presentations I
- Stephan Huckemann
Plenary
- Sven Bingert (GWDG)
Plenary
- Sven Bingert (GWDG)
Plenary
- Ramin Yahyapour
In Space Robotics Lab (SRL) at Tohoku University, Japan, we are developing heterogeneous multi-robot systems for lunar/planetary exploration. So far, robotic exploration missions on the surface of the Moon and remote planets have been conducted by a single capable mobile robot. But if deploying multiple robots, we expect advanced performance in terms of increased coverage areas, accuracy of...
Features measured from a protein ensemble, like atom distances, are often not recovered on average in molecular dynamics simulations due to imperfections in the simulated force fields. To remedy this problem, various ensemble refinement methods have been developed. We approach the problem from the maximum entropy point of view, in order to determine a least biased force field modification for...
We introduce AI Usage Cards, a standardized way to report the use of AI in scientific research. Our model and cards allow users to reflect on key principles of responsible AI usage. They also help the research community trace, compare, and question various forms of AI usage and support the development of accepted community norms.
Statistical inference in the field of phylogenetics requires the adaptiion of many classical methods to more general metric frameworks. The Fréchet-mean of a probability distribution is a generalisation of the expectation to metric spaces. It has been observed that the sample mean of certain probability distributions in Billera-Holmes-Vogtmann (BHV) phylogenetic spaces is confined to a...
KISSKI, a pioneering force in AI research and services, centres its efforts on sensitive and critical infrastructures. Collaborating with experts spanning medicine, energy, and AI domains, KISSKI is dedicated to forging a robust AI service centre. Its holistic range of provisions, encompassing hardware, software, consultancy, and training, is poised to empower SMEs, start-ups, and research...
This talk introduces our Moonshot project which is a project in the National Research and Development (R&D) program in Japan. The Moonshot program promotes high-risk, high-impact R&D aiming to achieve ambitious Moonshot Goals and solve issues facing future society such as super-aging populations. Our project is accepted under the Moonshot Goal 3: Realization of AI robots that autonomously...
In this talk, I will give an overview of ongoing and planned research of my new chair "Optimization and Biomechanics for Human-Centred Robotics" at KIT and my CERC "Human-Centred Robotics and Machine Intelligence" at the University of Waterloo.
Human-centred robots are predicted to have a large societal impact in the future, e.g. in form of humanoid robots supporting people in dangerous or...
The rapid advancement of Artificial Intelligence (AI) technologies has increased interest in their application within educational contexts. In particular, Short Answer Scoring (SAS), which focuses on the automated assessment of brief, descriptive answers, is attracting increasing attention. The primary reasons for researching SAS include reducing grading costs and facilitating real-time,...
Recently, the penalized regularization regression methods have been extensively studied in the literature, but it is still difficult to generalize a method to be applied in various applications, particularly that suffer from heterogeneity and collinearity. Due to that, we compare the developed machine learning methods using numerical simulations for various senario. The applied methods in this...
In medicine, artificial intelligence (AI) and machine learning (ML) promise vast advances. We start by providing an overview of current applications of AI and ML in cardiovascular medicine. Furthermore, we will provide an example for the development and validation of an explainable ML model from cardiovascular medicine. Finally, we discuss the role of statistics in AI/ML applications.
Alice Violaine Saletta, Gustavo Hernan Diaz, Shreya Santra and Kazuya Yoshida
Department of Aerospace Engineering, Tohoku University, Japan
“Teaching by showing” is a topic that has been widely explored in the history of robotics research. The idea of having a system that can understand what action is performed by a human using its sight and make a robot able to reproduce it is indeed an...
Despite their widespread adoption, the inner workings of Deep Neural Networks (DNNs) remain largely unknown. One key aspect of DNN learning is how the hidden layers' activation patterns encode the ground-truth label that the network is supposed to predict. This task-relevant information is represented jointly by groups of neurons within a layer. However, the specific way in which this mutual...
Current deep-learning-based AI allows integrating a lot of written material humans have created over generations and helps people in abstracting information, learning, making decisions, etc. However if this type of AI is directly transferable to robots is not yet clear. In order to act in some environment, robots have to cover the gap between continuous sensing and action on one side and the...
With the progress of machine learning and artificial intelligence, various research is being conducted in dentistry to support diagnosis and treatment, prevent medical errors, and improve patients' QOL by introducing these technologies. In order to infer the contents of dental treatment and acquire feature representations of surgeons’ behavior, the Joint Research Department for Oral Data...
Neural networks rely on coordination among individual neurons to perform complex tasks, but in the brain, they must operate within the constraints of locality for both computation and learning. Our research uses an information-theoretic approach to better understand how locality affects neural networks' structure and operation. We employ Partial Information Decomposition (PID) to quantify...
