Giambattista Parascandolo
Giambattista Parascandolo
PhD Student, Max Planck Institute for Intelligent Systems & ETH Zurich
Verified email at - Homepage
Cited by
Cited by
Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection
E Cakir*, G Parascandolo*, T Heittola, H Huttunen, T Virtanen
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017
Avoiding Discrimination through Causal Reasoning
N Kilbertus, M Rojas-Carulla, G Parascandolo, M Hardt, D Janzing, ...
NIPS 2017, 2017
Recurrent neural networks for polyphonic sound event detection in real life recordings
G Parascandolo, H Huttunen, T Virtanen
Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International …, 2016
DCASE 2016 acoustic scene classification using convolutional neural networks
M Valenti, A Diment, G Parascandolo, S Squartini, T Virtanen
IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and …, 2016
Sound event detection in multichannel audio using spatial and harmonic features
S Adavanne, G Parascandolo, P Pertilä, T Heittola, T Virtanen
arXiv preprint arXiv:1706.02293, 2017
Convolutional recurrent neural networks for bird audio detection
E Cakir, S Adavanne, G Parascandolo, K Drossos, T Virtanen
2017 25th European Signal Processing Conference (EUSIPCO), 1744-1748, 2017
A convolutional neural network approach for acoustic scene classification
M Valenti, S Squartini, A Diment, G Parascandolo, T Virtanen
2017 International Joint Conference on Neural Networks (IJCNN), 1547-1554, 2017
Learning Independent Causal Mechanisms
G Parascandolo, M Rojas-Carulla, N Kilbertus, B Schölkopf
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
Low latency sound source separation using convolutional recurrent neural networks
G Naithani, T Barker, G Parascandolo, L Bramsl, NH Pontoppidan, ...
2017 IEEE Workshop on Applications of Signal Processing to Audio and …, 2017
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
A Neitz, G Parascandolo, S Bauer, B Schölkopf
Neural Information Processing Systems (NIPS), 2018
Taming the waves: sine as activation function in deep neural networks
G Parascandolo, H Huttunen, T Virtanen
Generalization in anti-causal learning
N Kilbertus*, G Parascandolo*, B Schölkopf*
arXiv preprint arXiv:1812.00524, 2018
Low-latency sound source separation using deep neural networks
G Naithani, G Parascandolo, T Barker, NH Pontoppidan, T Virtanen
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016
Tempered Adversarial Networks
MSM Sajjadi, G Parascandolo, A Mehrjou, B Schölkopf
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
CONVWAVE: Searching for Gravitational Waves with Fully Convolutional Neural Nets
T Gebhard, N Kilbertus, G Parascandolo, I Harry, B Schölkopf
Workshop on Deep Learning for Physical Sciences, NIPS 2017, 2017
Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
G Parascandolo, L Buesing, J Merel, L Hasenclever, J Aslanides, ...
arXiv preprint arXiv:2004.11410, 2020
Learning explanations that are hard to vary
G Parascandolo, A Neitz, A Orvieto, L Gresele, B Schölkopf
arXiv preprint arXiv:2009.00329, 2020
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