Asja Fischer

According to our database1, Asja Fischer authored at least 47 papers between 2010 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2020
Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks.
Medical Image Anal., 2020

Improving the Long-Range Performance of Gated Graph Neural Networks.
CoRR, 2020

Characteristics of Monte Carlo Dropout in Wide Neural Networks.
CoRR, 2020

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions.
CoRR, 2020

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework.
CoRR, 2020

Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification.
CoRR, 2020

Unsupervised Cross-Domain Speech-to-Speech Conversion with Time-Frequency Consistency.
CoRR, 2020

Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery.
CoRR, 2020

Leveraging Frequency Analysis for Deep Fake Image Recognition.
CoRR, 2020

End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings.
CoRR, 2020

Algorithms for estimating the partition function of restricted Boltzmann machines.
Artif. Intell., 2020

Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs.
CoRR, 2019

Predictive Uncertainty Quantification with Compound Density Networks.
CoRR, 2019

Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs.
Proceedings of the Semantic Web - ISWC 2019, 2019

Pretrained Transformers for Simple Question Answering over Knowledge Graphs.
Proceedings of the Semantic Web - ISWC 2019, 2019

Incorporating Literals into Knowledge Graph Embeddings.
Proceedings of the Semantic Web - ISWC 2019, 2019

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Population-Contrastive-Divergence: Does consistency help with RBM training?
Pattern Recognit. Lett., 2018

Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters.
CoRR, 2018

Improving Response Selection in Multi-turn Dialogue Systems.
CoRR, 2018

DNN's Sharpest Directions Along the SGD Trajectory.
CoRR, 2018

On the regularization of Wasserstein GANs.
Proceedings of the 6th International Conference on Learning Representations, 2018

Finding Flatter Minima with SGD.
Proceedings of the 6th International Conference on Learning Representations, 2018

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge.
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018

2017
STDP-Compatible Approximation of Backpropagation in an Energy-Based Model.
Neural Computation, 2017

Graph-based predictable feature analysis.
Mach. Learn., 2017

Three Factors Influencing Minima in SGD.
CoRR, 2017

Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level.
Proceedings of the 26th International Conference on World Wide Web, 2017

A Closer Look at Memorization in Deep Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Nets Don't Learn via Memorization.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
How to Center Deep Boltzmann Machines.
J. Mach. Learn. Res., 2016

Bidirectional Helmholtz Machines.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines.
Theor. Comput. Sci., 2015

Training Restricted Boltzmann Machines.
Künstliche Intell., 2015

Training opposing directed models using geometric mean matching.
CoRR, 2015

An objective function for STDP.
CoRR, 2015

Difference Target Propagation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Training restricted Boltzmann machines: An introduction.
Pattern Recognit., 2014

2013
The flip-the-state transition operator for restricted Boltzmann machines.
Mach. Learn., 2013

How to Center Binary Restricted Boltzmann Machines.
CoRR, 2013

Approximation properties of DBNs with binary hidden units and real-valued visible units.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
An Introduction to Restricted Boltzmann Machines.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2012

2011
Bounding the Bias of Contrastive Divergence Learning.
Neural Computation, 2011

Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives.
Proceedings of the ESANN 2011, 2011

2010
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010


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