Search Results for author: Klaus Mueller

Found 18 papers, 6 papers with code

Infographics Wizard: Flexible Infographics Authoring and Design Exploration

1 code implementation21 Apr 2022 Anjul Tyagi, Jian Zhao, Pushkar Patel, Swasti Khurana, Klaus Mueller

With the help of designers, we propose a semi-automated infographic framework for general structured and flow-based infographic design generation.

Cascaded Debiasing : Studying the Cumulative Effect of Multiple Fairness-Enhancing Interventions

1 code implementation8 Feb 2022 Bhavya Ghai, Mihir Mishra, Klaus Mueller

Lastly, we offer a list of combinations of interventions that perform best for different fairness and utility metrics to aid the design of fair ML pipelines.

Fairness

User-Centric Semi-Automated Infographics Authoring and Recommendation

no code implementations26 Aug 2021 Anjul Tyagi, Jian Zhao, Pushkar Patel, Swasti Khurana, Klaus Mueller

Based on the framework, we also propose an interactive tool, \name{}, for assisting novice designers with creating high-quality infographics from an input in a markdown format by offering recommendations of different design components of infographics.

Fluent: An AI Augmented Writing Tool for People who Stutter

1 code implementation23 Aug 2021 Bhavya Ghai, Klaus Mueller

On hovering over any such word, Fluent presents a set of alternative words which have similar meaning but are easier to speak.

Active Learning

Transforming the Latent Space of StyleGAN for Real Face Editing

1 code implementation29 May 2021 Heyi Li, Jinlong Liu, Yunzhi Bai, Huayan Wang, Klaus Mueller

But more importantly, the proposed $W$++ space achieves superior performance in both reconstruction quality and editing quality.

Image Synthesis for Data Augmentation in Medical CT using Deep Reinforcement Learning

no code implementations18 Mar 2021 Arjun Krishna, Kedar Bartake, Chuang Niu, Ge Wang, Youfang Lai, Xun Jia, Klaus Mueller

Deep learning has shown great promise for CT image reconstruction, in particular to enable low dose imaging and integrated diagnostics.

Data Augmentation Image Generation +3

WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddings

1 code implementation5 Mar 2021 Bhavya Ghai, Md Naimul Hoque, Klaus Mueller

In this work, we present WordBias, an interactive visual tool designed to explore biases against intersectional groups encoded in static word embeddings.

Word Embeddings

Noise Entangled GAN For Low-Dose CT Simulation

no code implementations18 Feb 2021 Chuang Niu, Ge Wang, Pingkun Yan, Juergen Hahn, Youfang Lai, Xun Jia, Arjun Krishna, Klaus Mueller, Andreu Badal, KyleJ. Myers, Rongping Zeng

We propose a Noise Entangled GAN (NE-GAN) for simulating low-dose computed tomography (CT) images from a higher dose CT image.

Computed Tomography (CT)

Visual Steering for One-Shot Deep Neural Network Synthesis

no code implementations28 Sep 2020 Anjul Tyagi, Cong Xie, Klaus Mueller

To deal with the problem, we formulate the task of neural network architecture optimization as a graph space exploration, based on the one-shot architecture search technique.

Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation

no code implementations6 Sep 2020 Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Klaus Mueller

The similarity score between feature rankings provided by the annotator and the local model explanation is used to assign a weight to each corresponding committee model.

Active Learning Feature Importance

Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience

no code implementations24 Jan 2020 Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Rachel Bellamy, Klaus Mueller

We conducted an empirical study comparing the model learning outcomes, feedback content and experience with XAL, to that of traditional AL and coactive learning (providing the model's prediction without the explanation).

Active Learning

Interpreting Galaxy Deblender GAN from the Discriminator's Perspective

no code implementations17 Jan 2020 Heyi Li, Yuewei Lin, Klaus Mueller, Wei Xu

Using the Galaxy Zoo dataset we demonstrate that our method clearly reveals attention areas of the Discriminator when differentiating generated galaxy images from ground truth images.

Data Augmentation

Metal Artifact Reduction in Cone-Beam X-Ray CT via Ray Profile Correction

no code implementations6 Aug 2018 Sungsoo Ha, Klaus Mueller

We tested the proposed method with two clinical datasets that were both obtained during spine surgery.

Computed Tomography (CT) Metal Artifact Reduction

Beyond saliency: understanding convolutional neural networks from saliency prediction on layer-wise relevance propagation

2 code implementations22 Dec 2017 Heyi Li, Yunke Tian, Klaus Mueller, Xin Chen

In this paper, we propose a novel two-step understanding method, namely Salient Relevance (SR) map, which aims to shed light on how deep CNNs recognize images and learn features from areas, referred to as attention areas, therein.

Saliency Prediction

Visualizing Linguistic Shift

no code implementations20 Nov 2016 Salman Mahmood, Rami Al-Rfou, Klaus Mueller

Neural network based models are a very powerful tool for creating word embeddings, the objective of these models is to group similar words together.

Document Classification Language Modelling +3

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