research
∙
09/04/2023
FinDiff: Diffusion Models for Financial Tabular Data Generation
The sharing of microdata, such as fund holdings and derivative instrumen...
share
research
∙
07/04/2023
Ben-ge: Extending BigEarthNet with Geographical and Environmental Data
Deep learning methods have proven to be a powerful tool in the analysis ...
research
∙
06/19/2023
Partial Hypernetworks for Continual Learning
Hypernetworks mitigate forgetting in continual learning (CL) by generati...
research
∙
06/09/2023
Learning Emotional Representations from Imbalanced Speech Data for Speech Emotion Recognition and Emotional Text-to-Speech
Effective speech emotional representations play a key role in Speech Emo...
research
∙
04/26/2023
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models
With growing size of Neural Networks (NNs), model sparsification to redu...
research
∙
03/02/2023
Fine-grained Emotional Control of Text-To-Speech: Learning To Rank Inter- And Intra-Class Emotion Intensities
State-of-the-art Text-To-Speech (TTS) models are capable of producing hi...
research
∙
01/26/2023
Class-Incremental Learning with Repetition
Real-world data streams naturally include the repetition of previous con...
research
∙
10/26/2022
Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing
The International Standards on Auditing require auditors to collect reas...
research
∙
09/29/2022
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
In the last years, neural networks (NN) have evolved from laboratory env...
research
∙
09/29/2022
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Learning representations of neural network weights given a model zoo is ...
research
∙
09/19/2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations
Detecting accounting anomalies is a recurrent challenge in financial sta...
research
∙
08/26/2022
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits
The ongoing 'digital transformation' fundamentally changes audit evidenc...
research
∙
08/09/2022
Generative Data Augmentation Guided by Triplet Loss for Speech Emotion Recognition
Speech Emotion Recognition (SER) is crucial for human-computer interacti...
research
∙
07/22/2022
Hyper-Representations for Pre-Training and Transfer Learning
Learning representations of neural network weights given a model zoo is ...
research
∙
12/25/2021
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting Data
International audit standards require the direct assessment of a financi...
research
∙
12/07/2021
Saliency Diversified Deep Ensemble for Robustness to Adversaries
Deep learning models have shown incredible performance on numerous image...
research
∙
10/28/2021
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction
Self-Supervised Learning (SSL) has been shown to learn useful and inform...
research
∙
10/27/2021
Zero-shot Voice Conversion via Self-supervised Prosody Representation Learning
Voice Conversion (VC) for unseen speakers, also known as zero-shot VC, i...
research
∙
09/23/2021
Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit Tasks
International audit standards require the direct assessment of a financi...
research
∙
09/21/2021
Heterogeneous Ensemble for ESG Ratings Prediction
Over the past years, topics ranging from climate change to human rights ...
research
∙
09/21/2021
Learning Interpretable Concept Groups in CNNs
We propose a novel training methodology – Concept Group Learning (CGL) –...
research
∙
08/31/2021
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space
Air pollution is a major driver of climate change. Anthropogenic emissio...
research
∙
07/22/2021
Power Plant Classification from Remote Imaging with Deep Learning
Satellite remote imaging enables the detailed study of land use patterns...
research
∙
04/13/2021
NoiseVC: Towards High Quality Zero-Shot Voice Conversion
Voice conversion (VC) is a task that transforms voice from target audio ...
research
∙
03/26/2021
Continual Speaker Adaptation for Text-to-Speech Synthesis
Training a multi-speaker Text-to-Speech (TTS) model from scratch is comp...
research
∙
12/13/2020
Leaking Sensitive Financial Accounting Data in Plain Sight using Deep Autoencoder Neural Networks
Nowadays, organizations collect vast quantities of sensitive information...
research
∙
11/23/2020
Characterization of Industrial Smoke Plumes from Remote Sensing Data
The major driver of global warming has been identified as the anthropoge...
research
∙
11/12/2020
Using IPA-Based Tacotron for Data Efficient Cross-Lingual Speaker Adaptation and Pronunciation Enhancement
Recent neural Text-to-Speech (TTS) models have been shown to perform ver...
research
∙
08/06/2020
Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks
The audit of financial statements is designed to collect reasonable assu...
research
∙
07/15/2020
Facial Recognition: A cross-national Survey on Public Acceptance, Privacy, and Discrimination
With rapid advances in machine learning (ML), more of this technology is...
research
∙
06/18/2020
An Investigation of the Weight Space for Version Control of Neural Networks
Deployed Deep Neural Networks (DNNs) are often trained further to improv...
research
∙
05/04/2020
Neural Networks and Value at Risk
Utilizing a generative regime switching framework, we perform Monte-Carl...
research
∙
10/09/2019
Adversarial Learning of Deepfakes in Accounting
Nowadays, organizations collect vast quantities of accounting relevant t...
research
∙
08/02/2019
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks
The detection of fraud in accounting data is a long-standing challenge i...
research
∙
08/09/2018
Overcoming Missing and Incomplete Modalities with Generative Adversarial Networks for Building Footprint Segmentation
The integration of information acquired with different modalities, spati...
research
∙
03/22/2018
What do Deep Networks Like to See?
We propose a novel way to measure and understand convolutional neural ne...
research
∙
03/21/2018
Adversarial Defense based on Structure-to-Signal Autoencoders
Adversarial attack methods have demonstrated the fragility of deep neura...
research
∙
12/28/2017
Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Version)
Social multimedia users are increasingly sharing all kinds of data about...
research
∙
09/18/2017
Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks
The increased availability of high resolution satellite imagery allows t...
research
∙
09/15/2017
Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks
Learning to detect fraud in large-scale accounting data is one of the lo...
research
∙
07/25/2016
An Evolutionary Algorithm to Learn SPARQL Queries for Source-Target-Pairs: Finding Patterns for Human Associations in DBpedia
Efficient usage of the knowledge provided by the Linked Data community i...
research
∙
07/13/2016
AudioPairBank: Towards A Large-Scale Tag-Pair-Based Audio Content Analysis
Recently, sound recognition has been used to identify sounds, such as ca...
research
∙
11/21/2015
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets
We consider the visual sentiment task of mapping an image to an adjectiv...
research
∙
03/13/2015
The YLI-MED Corpus: Characteristics, Procedures, and Plans
The YLI Multimedia Event Detection corpus is a public-domain index of vi...
research
∙
02/11/2015
Large-Scale Deep Learning on the YFCC100M Dataset
We present a work-in-progress snapshot of learning with a 15 billion par...
research
∙
10/30/2014