Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing

19 October 2022

Bjoern W. Schuller

Papers citing "Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing"

45 / 45 papers shown

Title
Few-shot bioacoustic event detection at the DCASE 2022 challenge I. Nolasco S. Singh E. Vidana-Villa E. Grout J. Morford ... L. Gill H. Pamula Vincent Lostanlen V. Morfi D. Stowell 44 22 0 14 Jul 2022
Computational bioacoustics with deep learning: a review and roadmap D. Stowell 62 254 0 13 Dec 2021
AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling Alexandros Stergiou R. Poppe 81 81 0 01 Nov 2021
Seeing biodiversity: perspectives in machine learning for wildlife conservation D. Tuia B. Kellenberger Sara Beery Blair R. Costelloe Silvia Zuffi ... I. Couzin Grant Van Horn M. Crofoot Chuck Stewart T. Berger-Wolf 73 412 0 25 Oct 2021
Is MC Dropout Bayesian? Loic Le Folgoc V. Baltatzis S. Desai A. Devaraj S. Ellis O. M. Manzanera A. Nair Huaqi Qiu Julia A. Schnabel Ben Glocker BDL OOD UQCV 90 40 0 08 Oct 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 70 72 0 08 Jun 2021
Towards Citizen Science for Smart Cities: A Framework for a Collaborative Game of Bird Call Recognition Based on Internet of Sound Practices Emmanuel Rovithis N. Moustakas Konstantinos Vogklis Konstantinos Drossos Andreas Floros 18 4 0 31 Mar 2021
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise Jannik Schmitt Stefan Roth UQCV 38 6 0 15 Mar 2021
Uncertainty Propagation in Convolutional Neural Networks: Technical Report Christos Tzelepis Ioannis Patras UQCV 21 2 0 11 Feb 2021
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration Christian Tomani Florian Buettner UQCV AAML OOD 61 39 0 20 Dec 2020
A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features Vasilis Krokos V. Bui Xuan Stéphane P. A. Bordas P. Young P. Kerfriden 72 54 0 17 Dec 2020
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection Xiang Li Wenhai Wang Xiaolin Hu Jun Li Jinhui Tang Jian Yang ObjD 59 243 0 25 Nov 2020
Notes on the Behavior of MC Dropout Francesco Verdoja Ville Kyrki UQCV OOD BDL 48 37 0 06 Aug 2020
Does label smoothing mitigate label noise? Michal Lukasik Srinadh Bhojanapalli A. Menon Surinder Kumar NoLa 187 351 0 05 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 88 289 0 24 Feb 2020
The Case for Bayesian Deep Learning A. Wilson UQCV BDL OOD 118 113 0 29 Jan 2020
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition Qiuqiang Kong Yin Cao Turab Iqbal Yuxuan Wang Wenwu Wang Mark D. Plumbley VLM SSL 194 1,084 0 21 Dec 2019
LIP: Local Importance-based Pooling Ziteng Gao Limin Wang Gangshan Wu FAtt 70 96 0 12 Aug 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 76 41 0 27 Jun 2019
GIBBONFINDR: An R package for the detection and classification of acoustic signals Dena J. Clink Holger Klinck 33 6 0 06 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 147 247 0 06 Jun 2019
Attention-Augmented End-to-End Multi-Task Learning for Emotion Prediction from Speech Zixing Zhang Bingwen Wu Bjoern Schuller 54 83 0 29 Mar 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 96 809 0 07 Feb 2019
Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences Seonguk Seo Paul Hongsuck Seo Bohyung Han FedML UQCV BDL 123 76 0 28 Sep 2018
Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge D. Stowell Y. Stylianou Mike Wood H. Pamula H. Glotin 84 310 0 16 Jul 2018
Variance Networks: When Expectation Does Not Meet Your Expectations Kirill Neklyudov Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov UQCV 73 23 0 10 Mar 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 182 694 0 15 Nov 2017
Squeeze-and-Excitation Networks Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu 427 26,557 0 05 Sep 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,862 0 14 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,719 0 15 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 73 1,739 0 08 Mar 2017
Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables J. Daunizeau 32 40 0 01 Mar 2017
Learning From Noisy Large-Scale Datasets With Minimal Supervision Andreas Veit N. Alldrin Gal Chechik Ivan Krasin Abhinav Gupta Serge J. Belongie 139 480 0 06 Jan 2017
CNN Architectures for Large-Scale Audio Classification Shawn Hershey Sourish Chaudhuri D. Ellis J. Gemmeke A. Jansen ... Rif A. Saurous Bryan Seybold M. Slaney Ron J. Weiss K. Wilson 128 2,507 0 29 Sep 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 353 8,000 0 23 May 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 293 4,807 0 04 Jan 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,416 0 02 Dec 2015
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 413 7,969 0 17 Aug 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,517 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 852 9,346 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 364 19,733 0 09 Mar 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 578 27,327 0 01 Sep 2014