b'fortiss'

research

∙ 11/17/2016

Towards a Mathematical Understanding of the Difficulty in Learning with Feedforward Neural Networks

Training deep neural networks for solving machine learning problems is o...

Hao Shen, et al. ∙

research

∙ 04/28/2017

Maximum Resilience of Artificial Neural Networks

The deployment of Artificial Neural Networks (ANNs) in safety-critical a...

Chih-Hong Cheng, et al. ∙

research

∙ 10/09/2017

Verification of Binarized Neural Networks

We study the problem of formal verification of Binarized Neural Networks...

Chih-Hong Cheng, et al. ∙

research

∙ 10/09/2017

Verification of Binarized Neural Networks via Inter-Neuron Factoring

We study the problem of formal verification of Binarized Neural Networks...

Chih-Hong Cheng, et al. ∙

research

∙ 05/11/2018

Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems

Systematically testing models learned from neural networks remains a cru...

Chih-Hong Cheng, et al. ∙

research

∙ 06/06/2018

Towards Dependability Metrics for Neural Networks

Neural networks and other data engineered models are instrumental in dev...

Chih-Hong Cheng, et al. ∙

research

∙ 06/10/2018

ML + FV = ? A Survey on the Application of Machine Learning to Formal Verification

Formal Verification (FV) and Machine Learning (ML) can seem incompatible...

Moussa Amrani, et al. ∙

research

∙ 09/18/2018

Runtime Monitoring Neural Activation Patterns

For using neural networks in safety critical domains, it is important to...

Chih-Hong Cheng, et al. ∙

research

∙ 09/18/2018

Runtime Monitoring Neuron Activation Patterns

For using neural networks in safety critical domains, it is important to...

Chih-Hong Cheng, et al. ∙

research

∙ 11/12/2018

Compliance in Real Time Multiset Rewriting Models

The notion of compliance in Multiset Rewriting Models (MSR) has been int...

Max Kanovich, et al. ∙

research

∙ 11/26/2018

A Differential Topological View of Challenges in Learning with Feedforward Neural Networks

Among many unsolved puzzles in theories of Deep Neural Networks (DNNs), ...

Hao Shen, et al. ∙

research

∙ 12/17/2018

Traceability of Deep Neural Networks

[Context.] The success of deep learning makes its usage more and more te...

Vincent Aravantinos, et al. ∙

research

∙ 02/27/2019

Architecting Dependable Learning-enabled Autonomous Systems: A Survey

We provide a summary over architectural approaches that can be used to c...

Chih-Hong Cheng, et al. ∙

research

∙ 02/18/2019

A Generative Map for Image-based Camera Localization

In image-based camera localization systems, information about the enviro...

Mingpan Guo, et al. ∙

research

∙ 04/09/2019

Towards Safety Verification of Direct Perception Neural Networks

We study the problem of safety verification of direct perception neural ...

Chih-Hong Cheng, et al. ∙

research

∙ 09/25/2019

Generating Requirements Out of Thin Air: Towards Automated Feature Identification for New Apps

App store mining has proven to be a promising technique for requirements...

Tahira Iqbal, et al. ∙

research

∙ 03/06/2020

Lane-Merging Using Policy-based Reinforcement Learning and Post-Optimization

Many current behavior generation methods struggle to handle real-world t...

Patrick Hart, et al. ∙

research

∙ 03/25/2020

Robust Stochastic Bayesian Games for Behavior Space Coverage

A key challenge in multi-agent systems is the design of intelligent agen...

Julian Bernhard, et al. ∙

research

∙ 04/30/2020

Leveraging Context-awareness to Better Support the IoT Cloud-Edge Continuum

Novel Internet of Things (IoT) requirements derived from a broader inter...

Liliana I. Carvalho, et al. ∙

research

∙ 05/05/2020

A Cloud-Based Collaboration Platform for Model-Based Design of Cyber-Physical Systems

Businesses, particularly small and medium-sized enterprises, aiming to s...

Peter Gorm Larsen, et al. ∙

research

∙ 09/01/2020

toki: A Build- and Test-Platform for Prototyping and Evaluating Operating System Concepts in Real-Time Environments

Typically, even low-level operating system concepts, such as resource sh...

Oliver Horst, et al. ∙

research

∙ 02/01/2021

Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spaces

Distance-based dynamic texture recognition is an important research fiel...

Alexander Sagel, et al. ∙

research

∙ 07/23/2021

Type-based Enforcement of Infinitary Trace Properties for Java

A common approach to improve software quality is to use programming guid...

Serdar Erbatur, et al. ∙

research

∙ 08/30/2021

Vision for an Artefact-based Approach to Regulatory Requirements Engineering

Background: Nowadays, regulatory requirements engineering (regulatory RE...

Oleksandr Kosenkov, et al. ∙

research

∙ 10/08/2021

Mobile 3D Printing Robot Simulation with Viscoelastic Fluids

The system design and algorithm development of mobile 3D printing robots...

Uljad Berdica, et al. ∙

research

∙ 01/25/2022

Automating Safety and Security Co-Design through Semantically-Rich Architectural Patterns

During the design of safety-critical systems, safety and security engine...

Yuri Gil Dantas, et al. ∙

fortiss

Featured Researchers

Hao Shen

Chih-Hong Cheng

Vincent Aravantinos

Vivek Nigam

Harald Ruess

Julian Bernhard

Thomas Brunner

Chung-Hao Huang

Chuangjie Xu

Alexander Sagel

Yuri Gil Dantas

Towards a Mathematical Understanding of the Difficulty in Learning with Feedforward Neural Networks

Maximum Resilience of Artificial Neural Networks

Verification of Binarized Neural Networks

Verification of Binarized Neural Networks via Inter-Neuron Factoring

Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems

Towards Dependability Metrics for Neural Networks

ML + FV = ? A Survey on the Application of Machine Learning to Formal Verification

Runtime Monitoring Neural Activation Patterns

Runtime Monitoring Neuron Activation Patterns

Compliance in Real Time Multiset Rewriting Models

A Differential Topological View of Challenges in Learning with Feedforward Neural Networks

Traceability of Deep Neural Networks

Architecting Dependable Learning-enabled Autonomous Systems: A Survey

A Generative Map for Image-based Camera Localization

Towards Safety Verification of Direct Perception Neural Networks

Generating Requirements Out of Thin Air: Towards Automated Feature Identification for New Apps

Lane-Merging Using Policy-based Reinforcement Learning and Post-Optimization

Robust Stochastic Bayesian Games for Behavior Space Coverage

Leveraging Context-awareness to Better Support the IoT Cloud-Edge Continuum

A Cloud-Based Collaboration Platform for Model-Based Design of Cyber-Physical Systems

toki: A Build- and Test-Platform for Prototyping and Evaluating Operating System Concepts in Real-Time Environments

Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spaces

Type-based Enforcement of Infinitary Trace Properties for Java

Vision for an Artefact-based Approach to Regulatory Requirements Engineering

Mobile 3D Printing Robot Simulation with Viscoelastic Fluids

Automating Safety and Security Co-Design through Semantically-Rich Architectural Patterns