research
∙
05/02/2023
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
We study the problem of choosing algorithm hyper-parameters in unsupervi...
share
research
∙
11/25/2022
Learning General Audio Representations with Large-Scale Training of Patchout Audio Transformers
The success of supervised deep learning methods is largely due to their ...
research
∙
07/12/2022
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
In lifelong learning, an agent learns throughout its entire life without...
research
∙
06/07/2022
Few-Shot Learning by Dimensionality Reduction in Gradient Space
We introduce SubGD, a novel few-shot learning method which is based on t...
research
∙
05/24/2022
History Compression via Language Models in Reinforcement Learning
In a partially observable Markov decision process (POMDP), an agent typi...
research
∙
10/11/2021
Efficient Training of Audio Transformers with Patchout
The great success of transformer-based models in natural language proces...
research
∙
07/19/2021
Over-Parameterization and Generalization in Audio Classification
Convolutional Neural Networks (CNNs) have been dominating classification...
research
∙
05/26/2021
Receptive Field Regularization Techniques for Audio Classification and Tagging with Deep Convolutional Neural Networks
In this paper, we study the performance of variants of well-known Convol...
research
∙
11/05/2020
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping
Deep Neural Networks are known to be very demanding in terms of computin...
research
∙
07/27/2020
Receptive-Field Regularized CNNs for Music Classification and Tagging
Convolutional Neural Networks (CNNs) have been successfully used in vari...
research
∙
07/06/2020
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Data augmentation techniques have become standard practice in deep learn...
research
∙
10/28/2019
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs
We present CP-JKU submission to MediaEval 2019; a Receptive Field-(RF)-r...
research
∙
09/05/2019
Receptive-field-regularized CNN variants for acoustic scene classification
Acoustic scene classification and related tasks have been dominated by C...
research
∙
09/04/2019
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification
Distribution mismatches between the data seen at training and at applica...
research
∙
07/03/2019
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification
Convolutional Neural Networks (CNNs) have had great success in many mach...
research
∙
05/16/2019
On Conditioning GANs to Hierarchical Ontologies
The recent success of Generative Adversarial Networks (GAN) is a result ...
research
∙
10/31/2018
Mixture Density Generative Adversarial Networks
Generative Adversarial Networks have surprising ability for generating s...
research
∙
07/27/2018
Large-Scale Weakly Labeled Semi-Supervised Sound Event Detection in Domestic Environments
This paper presents DCASE 2018 task 4. The task evaluates systems for th...
research
∙
06/22/2018
Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data
Diagnosis and risk stratification of cancer and many other diseases requ...
research
∙
11/10/2017
Deep Within-Class Covariance Analysis for Acoustic Scene Classification
Within-Class Covariance Normalization (WCCN) is a powerful post-processi...
research
∙
08/06/2017
Probabilistic Generative Adversarial Networks
We introduce the Probabilistic Generative Adversarial Network (PGAN), a ...
research
∙
07/24/2017
Likelihood Estimation for Generative Adversarial Networks
We present a simple method for assessing the quality of generated images...
research
∙
06/20/2017