Giambattista Parascandolo
Giambattista Parascandolo
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Cited by
Cited by
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Avoiding Discrimination through Causal Reasoning
N Kilbertus, M Rojas-Carulla, G Parascandolo, M Hardt, D Janzing, ...
NIPS 2017, 2017
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
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
DCASE, 95-99, 2016
Learning Independent Causal Mechanisms
G Parascandolo, M Rojas-Carulla, N Kilbertus, B Schölkopf
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
Learning explanations that are hard to vary
G Parascandolo, A Neitz, A Orvieto, L Gresele, B Schölkopf
ICLR 2021, 2021
Neural Symbolic Regression that Scales
L Biggio, T Bendinelli, A Neitz, A Lucchi, G Parascandolo
ICML 2021, 2021
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
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
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*
NeurIPS 2018 Workshop on Critiquing and Correcting Trends in Machine Learning, 2018
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
A Neitz, G Parascandolo, S Bauer, B Schölkopf
Neural Information Processing Systems (NIPS), 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
Divide-and-Conquer Monte Carlo Tree Search
G Parascandolo, LH Buesing, J Merel, L Hasenclever, J Aslanides, ...
Tempered Adversarial Networks
MSM Sajjadi, G Parascandolo, A Mehrjou, B Schölkopf
Proceedings of the 35th International Conference on Machine Learning (ICML), 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
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
A Seq2Seq approach to Symbolic Regression
L Biggio, T Bendinelli, A Lucchi, G Parascandolo
NeurIPS 2020 Workshop "Knowledge Representation & Reasoning Meets Machine …, 2020
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Articles 1–20