Search Results for author: An Nguyen

Found 13 papers, 5 papers with code

Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks

1 code implementation18 Nov 2022 Thomas Altstidl, An Nguyen, Leo Schwinn, Franz Köferl, Christopher Mutschler, Björn Eskofier, Dario Zanca

We also demonstrate that our family of models is able to generalize well towards larger scales and improve scale equivariance.

Review of the AMLAS Methodology for Application in Healthcare

no code implementations1 Sep 2022 Shakir Laher, Carla Brackstone, Sara Reis, An Nguyen, Sean White, Ibrahim Habli

In recent years, the number of machine learning (ML) technologies gaining regulatory approval for healthcare has increased significantly allowing them to be placed on the market.

Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI

no code implementations4 May 2022 Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin

The ability to continuously process and retain new information like we do naturally as humans is a feat that is highly sought after when training neural networks.

Explainable Artificial Intelligence (XAI)

Language Model Evaluation in Open-ended Text Generation

no code implementations8 Aug 2021 An Nguyen

Although current state-of-the-art language models have achieved impressive results in numerous natural language processing tasks, still they could not solve the problem of producing repetitive, dull and sometimes inconsistent text in open-ended text generation.

Attribute Language Modelling +1

Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks

no code implementations21 May 2021 Leo Schwinn, René Raab, An Nguyen, Dario Zanca, Bjoern Eskofier

Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community.

Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis

1 code implementation24 Feb 2021 Leo Schwinn, An Nguyen, René Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Bjoern Eskofier

The susceptibility of deep neural networks to untrustworthy predictions, including out-of-distribution (OOD) data and adversarial examples, still prevent their widespread use in safety-critical applications.

System Design for a Data-driven and Explainable Customer Sentiment Monitor

1 code implementation11 Jan 2021 An Nguyen, Stefan Foerstel, Thomas Kittler, Andrey Kurzyukov, Leo Schwinn, Dario Zanca, Tobias Hipp, Da Jun Sun, Michael Schrapp, Eva Rothgang, Bjoern Eskofier

The overall framework is currently deployed, learns and evaluates predictive models from terabytes of IoT and enterprise data to actively monitor the customer sentiment for a fleet of thousands of high-end medical devices.

Interpretable Machine Learning Management

Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks

no code implementations5 Nov 2020 Leo Schwinn, An Nguyen, René Raab, Dario Zanca, Bjoern Eskofier, Daniel Tenbrinck, Martin Burger

We empirically show that by incorporating this nonlocal gradient information, we are able to give a more accurate estimation of the global descent direction on noisy and non-convex loss surfaces.

Adversarial Attack

Conformance Checking for a Medical Training Process Using Petri net Simulation and Sequence Alignment

1 code implementation21 Oct 2020 An Nguyen, Wenyu Zhang, Leo Schwinn, Bjoern Eskofier

Process Mining has recently gained popularity in healthcare due to its potential to provide a transparent, objective and data-based view on processes.

Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring

1 code implementation2 Oct 2020 An Nguyen, Srijeet Chatterjee, Sven Weinzierl, Leo Schwinn, Martin Matzner, Bjoern Eskofier

To better model the time dependencies between events, we propose a new PBPM technique based on time-aware LSTM (T-LSTM) cells.

ICE: Idiom and Collocation Extractor for Research and Education

no code implementations EACL 2017 Vasanthi Vuppuluri, Shahryar Baki, An Nguyen, Rakesh Verma

Collocation and idiom extraction are well-known challenges with many potential applications in Natural Language Processing (NLP).

POS Question Answering

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