A5075046917- Model-Driven Software Engineering Techniques
- Digital Innovation in Industries
- Quantum Computing Algorithms and Architecture
- Physics and Engineering Research Articles
- Software Testing and Debugging Techniques
- Business Process Modeling and Analysis
- Cosmology and Gravitation Theories
- Logic, programming, and type systems
- Formal Methods in Verification
- Flexible and Reconfigurable Manufacturing Systems
- Sports Science and Education
- Computational Physics and Python Applications
- Semantic Web and Ontologies
- Gaussian Processes and Bayesian Inference
- Advanced Neural Network Applications
- Libraries and Information Services
- Galaxies: Formation, Evolution, Phenomena
- Education Methods and Technologies
- Natural Language Processing Techniques
- Modeling and Simulation Systems
- Linguistic research and analysis
- Complexity and Algorithms in Graphs
- Quantum-Dot Cellular Automata
- Mathematics, Computing, and Information Processing
- Advanced Database Systems and Queries
Audi (Germany)
2022-2024
Mercedes-Benz (Germany)
2021-2022
Furtwangen University
2016-2021
Daimler (Germany)
2020
KLS Martin (Germany)
2020
Springer Nature (Germany)
2020
Takeda (Austria)
2019
Max Planck Institute for Astrophysics
2013-2018
Ludwig-Maximilians-Universität München
2015-2018
Medical University of Vienna
2011-2018
Research in machine learning, mobile robotics, and autonomous driving is accelerated by the availability of high quality annotated data. To this end, we release Audi Autonomous Driving Dataset (A2D2). Our dataset consists simultaneously recorded images 3D point clouds, together with bounding boxes, semantic segmentation, instance data extracted from automotive bus. sensor suite six cameras five LiDAR units, providing full 360 degree coverage. The time synchronized mutually registered....
Preexisting immunity against adeno-associated virus (AAV) is a major challenge facing AAV gene therapy, resulting in the exclusion of patients from clinical trials. Accordingly, proper assessment anti-AAV necessary for understanding data and product development. Previous studies on prevalence lack method standardization, rendering difficult. Addressing this need, we used assays that were validated according to guidelines comprehensive characterization anti-AAV1, -AAV2, -AAV5, -AAV8 large...
Patients with preexisting anti-adeno-associated virus serotype 8 (AAV8) neutralizing antibodies (NAbs) are currently excluded from AAV8 gene therapy trials. Therefore, the assessment of biologically relevant AAV8-NAb titers is critical for product development in therapy. However, standardized assays have not been routinely used to determine anti-AAV8-NAb titers, contributing a wide range reported anti-AAV8 prevalence rates. Using clinical vitro NAb assay separate study, higher than expected...
We reconstruct the 3D structure of magnetic fields, which were seeded by density perturbations during radiation dominated epoch Universe and later on evolved formation. To achieve this goal, we rely three dimensional initial fields inferred from 2M++ galaxy compilation via Bayesian $\texttt{BORG}$ algorithm. Using those, estimate magnetogenesis so called Harrison mechanism. This effect produced exploiting different photon drag electrons ions in vortical motions, are exited due to second...
We present a generic inference method for inflation models from observational data by the usage of higher-order statistics curvature perturbation on uniform density hypersurfaces. This is based calculation posterior primordial non-Gaussianity parameters fNL and gNL, which in general depend specific reheating models, enables to discriminate among still viable models. To keep analyticity as far possible dispense with numerically expensive sampling techniques saddle-point approximation...
Localizing objects in 3D space and understanding their associated properties is challenging given only monocular RGB images. The situation compounded by the loss of depth information during perspective projection. We present Center3D, a one-stage anchor-free approach, to efficiently estimate location using By exploiting difference between 2D centers, we are able consistently. Center3D uses combination classification regression understand hidden more robustly than each method alone. Our...
The application of antisense molecules, such as morpholino oligonucleotides, is an efficient method gene inactivation in vivo. We recently introduced phosphonic ester modified peptide nucleic acids (PNA) for vivo loss-of-function experiments medaka embryos. Here we tested novel modifications the PNA backbone to knockdown tcf3 gene.A single exists genome and its strongly affected eye development embryos, leading size reduction anophthalmia severe cases. function Tcf3 depends on co-repressor...
For automotive applications, the Graph Attention Network (GAT) is a prominently used architecture to include relational information of traffic scenario during feature embedding. As shown in this work, however, one most popular GAT realizations, namely GATv2, has potential pitfalls that hinder an optimal parameter learning. Especially for small and sparse graph structures proper optimization problematic. To surpass limitations, work proposes architectural modifications GATv2. In controlled...
Abstract Background Synthetic antisense molecules have an enormous potential for therapeutic applications in humans. The major aim of such strategies is to specifically interfere with gene function, thus modulating cellular pathways according the demands. Among which can block mRNA function a sequence specific manner are peptide nucleic acids (PNA). They highly stable and efficiently selectively interact RNA. However, some properties non-modified aminoethyl glycine PNAs (aegPNA) hamper their...
Matrix determinants play an important role in data analysis, particular when Gaussian processes are involved. Due to currently exploding volumes, linear operations-matrices-acting on the often not accessible directly but only represented indirectly form of a computer routine. Such routine implements transformation vector undergoes under matrix multiplication. While efficient probing routines estimate matrix's diagonal or trace, based solely such computationally affordable matrix-vector...
We study the quantum complexity of algorithms for optimal graph traversal problems. look at eulerian tours, postman approximation travelling salesman tours and self avoiding walks. present lower bounds these Our results improve best classical corresponding
We present charm (cosmic history agnostic reconstruction method), a novel inference algorithm that reconstructs the cosmic expansion as encoded in Hubble parameter $H(z)$ from SNe Ia data. The novelty of approach lies usage information field theory, statistical theory is very well suited for construction optimal signal recovery algorithms. infers non-parametrically $s(a)=\ln(\rho(a)/\rho_{\mathrm{crit}0})$, density evolution which determines $H(z)$, without assuming an analytical form...
Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is known to activate the canonical NF-κB pathway similar TNF. The exact mechanism of entire signaling cascade still under investigation. involvement linear ubiquitylation as upregulating component has already been shown recently in some cell lines, but not human embryonic kidney 293 (HEK293) cells. downregulating function ABIN-1 (A20 binding and inhibitor NF-κB) antagonist combination with NF-κB-inducing pathways, TRAIL....
We present the first realization of an assembly sequence planning framework for large-scale and complex 3D real-world CAD scenarios. Other than in academic benchmark data sets, our scenario each assembled part is allowed to contain flexible fastening elements number parts quite high. With we are able derive a meaningful priority graph parts. Our divides disassembly motion into NEAR- subsequent FAR phase uses existing specialized planners phase. To reduce unsuccessful requests use general...
We present an error-diagnostic validation method for posterior distributions in Bayesian signal inference, advancement of a previous work. It transfers deviations from the correct into characteristic uniform distribution quantity constructed this purpose. show that is able to reveal and discriminate several kinds numerical approximation errors, as well their impact on distribution. For we four typical analytical examples posteriors with incorrect variance, skewness, position maximum, or...
The calibration of a measurement device is crucial for every scientific experiment, where signal has to be inferred from data. We present CURE, the calibration-uncertainty renormalized estimator, reconstruct and simultaneously instrument's same data without knowing exact calibration, but its covariance structure. idea CURE method, developed in framework information field theory, start with an assumed successively include more portions uncertainty into inference equations absorb resulting...
We present an approximate calculation of the full Bayesian posterior probability distribution for local non-Gaussianity parameter ${f}_{\mathrm{nl}}$ from observations cosmic microwave background anisotropies within framework information field theory. The approximation that we introduce allows us to dispense with numerically expensive sampling techniques. use a novel validation method (DIP test) in cosmology test precision our method. It transfers inaccuracies calculated into deviations...