7.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of KaiserslauternDE112 papers
- University of Koblenz and LandauDE28 papers
- German Research Centre for Artificial IntelligenceDE25 papers
- Fraunhofer Institute for Industrial MathematicsDE13 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- Johannes Gutenberg University MainzDE8 papers
- Ludwig-Maximilians-Universität MünchenDE7 papers
- RWTH Aachen UniversityDE7 papers
- Daimler (Germany)DE6 papers
- Sorbonne UniversitéFR6 papers
- Universidad Autónoma de MadridES6 papers
- Universität HamburgDE6 papers
10 papers · 1 filter
Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detection
Jennifer Werner, Justus Arweiler, Indra Jungjohann +4
Anomaly detection (AD) in chemical processes based on deep learning offers significant opportunities but requires large, diverse, and well-annotated training datasets that are rare…
GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures
Marco Hoffmann, Hans Hasse, Fabian Jirasek
Although the pure component vapor pressure is one of the most important properties for designing chemical processes, no broadly applicable, sufficiently accurate, and open-source p…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1168
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
HANNA: Hard-constraint Neural Network for Consistent Activity Coefficient Prediction
Thomas Specht, Mayank Nagda, Sophie Fellenz +3
We present the first hard-constraint neural network for predicting activity coefficients (HANNA), a thermodynamic mixture property that is the basis for many applications in scienc…
Unimodal and Multimodal Sensor Fusion for Wearable Activity Recognition
Hymalai Bello
Combining different sensing modalities with multiple positions helps form a unified perception and understanding of complex situations such as human behavior. Hence, human activity…
Linearly-scalable learning of smooth low-dimensional patterns with permutation-aided entropic dimension reduction
Illia Horenko, Lukas Pospisil
In many data science applications, the objective is to extract appropriately-ordered smooth low-dimensional data patterns from high-dimensional data sets. This is challenging since…
CaptAinGlove: Capacitive and Inertial Fusion-Based Glove for Real-Time on Edge Hand Gesture Recognition for Drone Control
Hymalai Bello, Sungho Suh, Daniel Geißler +3
We present CaptAinGlove, a textile-based, low-power (1.15Watts), privacy-conscious, real-time on-the-edge (RTE) glove-based solution with a tiny memory footprint (2MB), designed to…
InMyFace: Inertial and Mechanomyography-Based Sensor Fusion for Wearable Facial Activity Recognition
Hymalai Bello, Luis Alfredo Sanchez Marin, Sungho Suh +2
Recognizing facial activity is a well-understood (but non-trivial) computer vision problem. However, reliable solutions require a camera with a good view of the face, which is ofte…
Privacy Meets Explainability: A Comprehensive Impact Benchmark
Saifullah Saifullah, Dominique Mercier, Adriano Lucieri +2
Since the mid-10s, the era of Deep Learning (DL) has continued to this day, bringing forth new superlatives and innovations each year. Nevertheless, the speed with which these inno…
Neural Transformation Learning for Deep Anomaly Detection Beyond Images
Chen Qiu, Timo Pfrommer, Marius Kloft +2
Data transformations (e.g. rotations, reflections, and cropping) play an important role in self-supervised learning. Typically, images are transformed into different views, and neu…