Isik, L., Tacchetti, A. & Poggio, T. A fast, invariant representation for human action in the visual system. Journal of Neurophysiology (2018). doi:https://doi.org/10.1152/jn.00642.2017

Tacchetti, A., Isik, L. & Poggio, T. Invariant Recognition Shapes Neural Representations of Visual Input. Annual Review of Vision Science 4, 403 - 422 (2018).

Isik, L. & Tacchetti, A. MEG action recognition data. (2018). doi:https://doi.org/10.7910/DVN/KFYY2M

Tacchetti, A., Voinea, S. & Evangelopoulos, G. Trading robust representations for sample complexity through self-supervised visual experience. Advances in Neural Information Processing Systems 31 (Bengio, S. et al.) 9640?9650 (Curran Associates, Inc., 2018). at <http://papers.nips.cc/paper/8170-trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf>

Tacchetti, A., Voinea, S. & Evangelopoulos, G. Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets. (2017).

Isik, L., Tacchetti, A. & Poggio, T. A fast, invariant representation for human action in the visual system. J Neurophysiol jn.00642.2017 (2017). doi:10.1152/jn.00642.2017

Tacchetti, A., Isik, L. & Poggio, T. Invariant action recognition dataset. (2017). at <https://doi.org/10.7910/DVN/DMT0PG>

Tacchetti, A., Isik, L. & Poggio, T. Invariant recognition drives neural representations of action sequences. PLoS Comp. Bio (2017).

Tacchetti, A., Isik, L. & Poggio, T. Invariant recognition drives neural representations of action sequences. PLOS Computational Biology 13, e1005859 (2017).

Mutch, J. et al. Computational and Cognitive Neuroscience of Vision 85-104 (Springer, 2017).

Tacchetti, A., Voinea, S., Evangelopoulos, G. & Poggio, T. Representation Learning from Orbit Sets for One-shot Classification. AAAI Spring Symposium Series, Science of Intelligence (2017). at <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15357>

Isik, L., Tacchetti, A. & Poggio, T. Fast, invariant representation for human action in the visual system. (2016). at <http://arxiv.org/abs/1601.01358>

Tacchetti, A., Isik, L. & Poggio, T. Spatio-temporal convolutional networks explain neural representations of human actions. (2016).

Tacchetti, A., Isik, L. & Poggio, T. Invariant representations for action recognition in the visual system. Vision Sciences Society 15, (2015).

Isik, L., Tacchetti, A. & Poggio, T. Invariant representations for action recognition in the visual system. Computational and Systems Neuroscience (2015).

Anselmi, F. et al. Unsupervised learning of invariant representations. Theoretical Computer Science (2015). doi:10.1016/j.tcs.2015.06.048

Anselmi, F. et al. Unsupervised learning of invariant representations with low sample complexity: the magic of sensory cortex or a new framework for machine learning?. (2014).

Anselmi, F. et al. Unsupervised Learning of Invariant Representations in Hierarchical Architectures. (2013).