A guide to convolution arithmetic for deep learning V Dumoulin, F Visin arXiv preprint arXiv:1603.07285, 2016 | 2479 | 2016 |
Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 1086* | 2016 |
Pixelvae: A latent variable model for natural images I Gulrajani, K Kumar, F Ahmed, AA Taiga, F Visin, D Vazquez, A Courville arXiv preprint arXiv:1611.05013, 2016 | 389 | 2016 |
Reseg: A recurrent neural network-based model for semantic segmentation F Visin, M Ciccone, A Romero, K Kastner, K Cho, Y Bengio, M Matteucci, ... Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 385* | 2016 |
Renet: A recurrent neural network based alternative to convolutional networks F Visin, K Kastner, K Cho, M Matteucci, A Courville, Y Bengio arXiv preprint arXiv:1505.00393, 2015 | 338 | 2015 |
Continual unsupervised representation learning D Rao, F Visin, A Rusu, R Pascanu, YW Teh, R Hadsell Advances in neural information processing systems 32, 2019 | 284 | 2019 |
Meta-learning with warped gradient descent S Flennerhag, AA Rusu, R Pascanu, F Visin, H Yin, R Hadsell arXiv preprint arXiv:1909.00025, 2019 | 240 | 2019 |
Mollifying networks C Gulcehre, M Moczulski, F Visin, Y Bengio arXiv preprint arXiv:1608.04980, 2016 | 62 | 2016 |
Small data, big decisions: Model selection in the small-data regime J Bornschein, F Visin, S Osindero International conference on machine learning, 1035-1044, 2020 | 43 | 2020 |
Multi-view stereo with single-view semantic mesh refinement A Romanoni, M Ciccone, F Visin, M Matteucci Proceedings of the IEEE international conference on computer vision …, 2017 | 27 | 2017 |
Temporal difference uncertainties as a signal for exploration S Flennerhag, JX Wang, P Sprechmann, F Visin, A Galashov, ... arXiv preprint arXiv:2010.02255, 2020 | 15 | 2020 |
Learning rich touch representations through cross-modal self-supervision M Zambelli, Y Aytar, F Visin, Y Zhou, R Hadsell Conference on Robot Learning, 1415-1425, 2021 | 13 | 2021 |
Dataset loaders: a python library to load and preprocess datasets F Visin, A Romero https://github.com/fvisin/dataset_loaders, 2016 | 4 | 2016 |
ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation F Lattari, M Ciccone, M Matteucci, J Masci, F Visin arXiv preprint arXiv:1806.05510, 2018 | 2 | 2018 |
Deep recurrent neural networks for visual scene understanding F Visin Politecnico di Milano, 2017 | 1 | 2017 |
Main loop TF: a main loop for Tensorflow and custom data F Visin https://github.com/fvisin/main_loop_tf, 2017 | | 2017 |
Learning rich touch representations through cross-modal self-supervision Supplementary material M Zambelli, Y Aytar, F Visin, Y Zhou, R Hadsell | | |