Dynamic Variational Autoencoders for Visual Process Modeling

This work studies the problem of modeling visual processes by leveraging deep generative architectures for learning linear, Gaussian representations from observed sequences. We propose a joint learning framework, combining a vector autoregressive model and Variational Autoencoders. This results in an architecture that allows Variational Autoencoders to simultaneously learn a non-linear observation as well as a linear state model from sequences of frames. We validate our approach on artificial sequences and dynamic textures

SUB-DIP: Optimization on a subspace with deep image prior regularization and application to superresolution

International audienc

Incidence of maternal Toxoplasma infections in pregnancy in Upper Austria, 2000-2007

Sagel U, Krämer A, Mikolajczyk RT. Incidence of maternal Toxoplasma infections in pregnancy in Upper Austria, 2000-2007. BMC Infectious Diseases. 2011;11(1): 348.UNLABELLED: ABSTRACT: BACKGROUND: Despite three decades of prenatal screening program for toxoplasmosis in Austria, population-based estimates for the incidence of maternal infections with Toxoplasma gondii during pregnancy are lacking. We studied the incidence of primary maternal infections during pregnancy in the Federal State of Upper Austria. METHODS: Screening tests for 63,416 women and over 90,000 pregnancies (more than 84.5% of pregnancies in the studied region) in the time period between 01.01.2000 and 31.12.2007 were analysed. The incidence of toxoplasmosis was estimated indirectly by binomial and directly by interval censored regression. RESULTS: During the studied period, 66 acute infections (risk of 0.07% per pregnancy) were detected, but only 29.8% of seronegative women were tested at least three times during their pregnancies. The seroprevalence of Toxoplasma antibodies among all tested women was 31%. Indirectly estimated incidence (from differences in prevalence by age) was 0.5% per pregnancy, while directly estimated incidence (interval censored regression) was 0.17% per pregnancy (95% confidence interval: 0.13-0.21%). CONCLUSIONS: Calculating incidence from observed infections results in severe underreporting due to many missed tests and potential diagnostic problems. Using statistical modelling, we estimated primary toxoplasmosis to occur in 0.17% (0.13-0.21%) of all pregnancies in Upper Austria

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

The existence of representative datasets is a prerequisite of many successful artificial intelligence and machine learning models. However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training. The reasons for this are manifold and range from time and cost constraints to ethical considerations. As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge. Leveraging additional, already existing sources of knowledge is key to overcome the limitations of purely data-driven approaches, and eventually to increase the generalization capability of these models. Furthermore, predictions that conform with knowledge are crucial for making trustworthy and safe decisions even in underrepresented scenarios. This work provides an overview of existing techniques and methods in the literature that combine data-based models with existing knowledge. The identified approaches are structured according to the categories integration, extraction and conformity. Special attention is given to applications in the field of autonomous driving

Using mandatory data collection on multiresistant bacteria for internal surveillance in a hospital

Sagel U, Mikolajczyk RT, Krämer A. Using mandatory data collection on multiresistant bacteria for internal surveillance in a hospital. Methods of Information in Medicine. 2004;43(5):483-485.Objectives: Multiresistant pathogens cause major clinical problems and considerably increase treatment costs. Since 2001 the Protection Against Infection Act (PIA) obligates hospitals in Germany to the documentation of multiresistant bacteria. We analyzed the use of these data for routine internal surveillance. Methods: We used standard data collected for the mandatory documentation and studied consecutive diagnoses of Methicillin-resistant Staphylococcus aureus (MRSA) in a 893-bed tertiary level hospital in North Rhine-Westphalia in Germany. Based on the Poisson distribution for the cumulative yearly incidence of MRSA, we defined a threshold level for an outbreak. Results: During a 12-month time period 80 patients were diagnosed with MRSA. The time structure and spatial distribution of different MRSA phenotypes (defined through specific antibiotic resistance patterns) were consistent with the within-hospital transmission. In the two preceding time periods of 12 months each, 15 respectively 8 patients with MRSA were found. The defined alert threshold level for cumulative yearly incidence was crossed in the beginnings of the outbreak. Conclusion: Monitoring the mandatory data collected on multiresistant bacteria allows the early detection of accumulations suspect for the within-hospital transmission. This knowledge can be used for a fast reaction and breaking off the transmission chains