Siemens AG

∙ München , Germany ∙ 0 followers

The principal divisions of the company are Industry, Energy, Healthcare, and Infrastructure & Cities, which represent the main activities of the company.

Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck

In this paper, we present an in-depth investigation of the convolutional...
11/18/2019 ∙ by Ilja Manakov, et al. ∙ 35 ∙ share

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Industrial Federated Learning – Requirements and System Design

Federated Learning (FL) is a very promising approach for improving decen...
05/14/2020 ∙ by Thomas Hiessl, et al. ∙ 17 ∙ share

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ViewSynth: Learning Local Features from Depth using View Synthesis

We address the problem of jointly detecting keypoints and learning descr...
11/22/2019 ∙ by Jisan Mahmud, et al. ∙ 14 ∙ share

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Learning Neural PDE Solvers with Convergence Guarantees

Partial differential equations (PDEs) are widely used across the physica...
06/04/2019 ∙ by Jun-Ting Hsieh, et al. ∙ 13 ∙ share

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Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning

We tune one of the most common heating, ventilation, and air conditionin...
06/28/2019 ∙ by Marcello Fiducioso, et al. ∙ 3 ∙ share

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PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs

Deep generative models are proven to be a useful tool for automatic desi...
02/26/2020 ∙ by Wei Chen, et al. ∙ 3 ∙ share

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Table-Top Scene Analysis Using Knowledge-Supervised MCMC

In this paper, we propose a probabilistic method to generate abstract sc...
02/19/2020 ∙ by Ziyuan Liu, et al. ∙ 1 ∙ share

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InverseNet: Solving Inverse Problems with Splitting Networks

We propose a new method that uses deep learning techniques to solve the ...
12/01/2017 ∙ by Kai Fan, et al. ∙ 0 ∙ share

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Tensor Decompositions for Modeling Inverse Dynamics

Modeling inverse dynamics is crucial for accurate feedforward robot cont...
11/13/2017 ∙ by Stephan Baier, et al. ∙ 0 ∙ share

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Zero-Shot Deep Domain Adaptation

The existing methods of domain adaptation (DA) work under the assumption...
07/06/2017 ∙ by Kuan-Chuan Peng, et al. ∙ 0 ∙ share

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Two-Stream RNN/CNN for Action Recognition in 3D Videos

The recognition of actions from video sequences has many applications in...
03/22/2017 ∙ by Rui Zhao, et al. ∙ 0 ∙ share

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DepthSynth: Real-Time Realistic Synthetic Data Generation from CAD Models for 2.5D Recognition

Recent progress in computer vision has been dominated by deep neural net...
02/27/2017 ∙ by Benjamin Planche, et al. ∙ 0 ∙ share

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Type-Constrained Representation Learning in Knowledge Graphs

Large knowledge graphs increasingly add value to various applications th...
08/11/2015 ∙ by Denis Krompass, et al. ∙ 0 ∙ share

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Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

We present an algorithm for model-based reinforcement learning that comb...
05/23/2016 ∙ by Stefan Depeweg, et al. ∙ 0 ∙ share

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Proximal gradient method for huberized support vector machine

The Support Vector Machine (SVM) has been used in a wide variety of clas...
11/30/2015 ∙ by Yangyang Xu, et al. ∙ 0 ∙ share

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Towards a New Science of a Clinical Data Intelligence

In this paper we define Clinical Data Intelligence as the analysis of da...
11/17/2013 ∙ by Volker Tresp, et al. ∙ 0 ∙ share

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An Octree-Based Approach towards Efficient Variational Range Data Fusion

Volume-based reconstruction is usually expensive both in terms of memory...
08/26/2016 ∙ by Wadim Kehl, et al. ∙ 0 ∙ share

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A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

Person re-identification (re-id) is a critical problem in video analytic...
05/31/2016 ∙ by Srikrishna Karanam, et al. ∙ 0 ∙ share

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Fast 3D Salient Region Detection in Medical Images using GPUs

Automated detection of visually salient regions is an active area of res...
10/24/2013 ∙ by Rahul Thota, et al. ∙ 0 ∙ share

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Combinatorial Continuous Maximal Flows

Maximum flow (and minimum cut) algorithms have had a strong impact on co...
10/13/2010 ∙ by Camille Couprie, et al. ∙ 0 ∙ share

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Combining Recurrent and Convolutional Neural Networks for Relation Classification

This paper investigates two different neural architectures for the task ...
05/24/2016 ∙ by Ngoc Thang Vu, et al. ∙ 0 ∙ share

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Hierarchical Latent Word Clustering

This paper presents a new Bayesian non-parametric model by extending the...
01/20/2016 ∙ by Halid Ziya Yerebakan, et al. ∙ 0 ∙ share

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Look Mum, no VM Exits! (Almost)

Multi-core CPUs are a standard component in many modern embedded systems...
05/19/2017 ∙ by Ralf Ramsauer, et al. ∙ 0 ∙ share

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A Systematic Review of Productivity Factors in Software Development

Analysing and improving productivity has been one of the main goals of s...
01/19/2018 ∙ by Stefan Wagner, et al. ∙ 0 ∙ share

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Tell Me Where to Look: Guided Attention Inference Network

Weakly supervised learning with only coarse labels can obtain visual exp...
02/27/2018 ∙ by Kunpeng Li, et al. ∙ 0 ∙ share

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Robust Odometry using Sensor Consensus Analysis

Odometry forms an important component of many manned and autonomous syst...
03/06/2018 ∙ by Andrew W. Palmer, et al. ∙ 0 ∙ share

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Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies,...
04/29/2018 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

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Joint Bootstrapping Machines for High Confidence Relation Extraction

Semi-supervised bootstrapping techniques for relationship extraction fro...
05/01/2018 ∙ by Pankaj Gupta, et al. ∙ 0 ∙ share

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Replicated Siamese LSTM in Ticketing System for Similarity Learning and Retrieval in Asymmetric Texts

The goal of our industrial ticketing system is to retrieve a relevant so...
07/08/2018 ∙ by Pankaj Gupta, et al. ∙ 0 ∙ share

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Needs and Challenges for a Platform to Support Large-scale Requirements Engineering. A Multiple Case Study

Background: Requirement engineering is often considered a critical activ...
08/07/2018 ∙ by Davide Fucci, et al. ∙ 0 ∙ share

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Measuring the Temporal Behavior of Real-World Person Re-Identification

Designing real-world person re-identification (re-id) systems requires a...
08/16/2018 ∙ by Meng Zheng, et al. ∙ 0 ∙ share

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Improving Information Extraction from Images with Learned Semantic Models

Many applications require an understanding of an image that goes beyond ...
08/27/2018 ∙ by Stephan Baier, et al. ∙ 0 ∙ share

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dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning

Learning graph representations is a fundamental task aimed at capturing ...
09/07/2018 ∙ by Palash Goyal, et al. ∙ 0 ∙ share

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Energy-Based Hindsight Experience Prioritization

In Hindsight Experience Replay (HER), a reinforcement learning agent is ...
10/02/2018 ∙ by Rui Zhao, et al. ∙ 0 ∙ share

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Neural Relation Extraction Within and Across Sentence Boundaries

Past work in relation extraction mostly focuses on binary relation betwe...
10/11/2018 ∙ by Pankaj Gupta, et al. ∙ 0 ∙ share

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Reducing Visual Confusion with Discriminative Attention

Recent developments in gradient-based attention modeling have led to imp...
11/19/2018 ∙ by Lezi Wang, et al. ∙ 0 ∙ share

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Learning without Memorizing

Incremental learning (IL) is an important task aimed to increase the cap...
11/20/2018 ∙ by Prithviraj Dhar, et al. ∙ 0 ∙ share

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DynamicGEM: A Library for Dynamic Graph Embedding Methods

DynamicGEM is an open-source Python library for learning node representa...
11/26/2018 ∙ by Palash Goyal, et al. ∙ 0 ∙ share

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Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks

To date, the simulation of organ deformations for applications like ther...
12/13/2018 ∙ by Felix Meister, et al. ∙ 0 ∙ share

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Generic Primitive Detection in Point Clouds Using Novel Minimal Quadric Fits

We present a novel and effective method for detecting 3D primitives in c...
01/04/2019 ∙ by Tolga Birdal, et al. ∙ 0 ∙ share

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Using adjoint CFD to quantify the impact of manufacturing variations on a heavy duty turbine vane

We consider the evaluation of manufacturing variations to the aerodynami...
01/25/2019 ∙ by Alexander Liefke, et al. ∙ 0 ∙ share

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Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm

From formal and practical analysis, we identify new challenges that self...
02/13/2019 ∙ by Thomas Gabor, et al. ∙ 0 ∙ share

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Finding Robust Itemsets Under Subsampling

Mining frequent patterns is plagued by the problem of pattern explosion ...
02/18/2019 ∙ by Nikolaj Tatti, et al. ∙ 0 ∙ share

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Curiosity-Driven Experience Prioritization via Density Estimation

In Reinforcement Learning (RL), an agent explores the environment and co...
02/20/2019 ∙ by Rui Zhao, et al. ∙ 0 ∙ share

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Rule-Based Translation of Application-Level QoS Constraints into SDN Configurations for the IoT

In this paper, we propose an approach for the automated translation of a...
03/22/2019 ∙ by Jan Seeger, et al. ∙ 0 ∙ share

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Degrees of Laziness in Grounding: Effects of Lazy-Grounding Strategies on ASP Solving

The traditional ground-and-solve approach to Answer Set Programming (ASP...
03/29/2019 ∙ by Richard Taupe, et al. ∙ 0 ∙ share

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FECBench: A Holistic Interference-aware Approach for Application Performance Modeling

Services hosted in multi-tenant cloud platforms often encounter performa...
04/11/2019 ∙ by Yogesh D. Barve, et al. ∙ 0 ∙ share

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P4BFT: Hardware-Accelerated Byzantine-Resilient Network Control Plane

Byzantine Fault Tolerance (BFT) enables correct operation of distributed...
05/10/2019 ∙ by Ermin Sakic, et al. ∙ 0 ∙ share

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Pykg2vec: A Python Library for Knowledge Graph Embedding

Pykg2vec is an open-source Python library for learning the representatio...
06/04/2019 ∙ by Shih Yuan Yu, et al. ∙ 0 ∙ share

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Optimally Self-Healing IoT Choreographies

In the industrial Internet of Things domain, applications are moving fro...
07/10/2019 ∙ by Jan Seeger, et al. ∙ 0 ∙ share

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