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Andrea Tacchetti
Titolo
Citata da
Citata da
Anno
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
31532018
Visual interaction networks: Learning a physics simulator from video
N Watters, D Zoran, T Weber, P Battaglia, R Pascanu, A Tacchetti
Advances in neural information processing systems 30, 2017
3752017
Relational inductive biases, deep learning, and graph networks. arXiv 2018
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
1592018
Unsupervised learning of invariant representations
F Anselmi, JZ Leibo, L Rosasco, J Mutch, A Tacchetti, T Poggio
Theoretical Computer Science 633, 112-121, 2016
1382016
Unsupervised learning of invariant representations in hierarchical architectures
F Anselmi, JZ Leibo, L Rosasco, J Mutch, A Tacchetti, T Poggio
arXiv preprint arXiv:1311.4158, 2013
852013
Relational forward models for multi-agent learning
A Tacchetti, HF Song, PAM Mediano, V Zambaldi, NC Rabinowitz, ...
arXiv preprint arXiv:1809.11044, 2018
792018
GURLS: A Least Squares Library for Supervised Learning
A Tacchetti, P Mallapragada, M Santoro, R Rosasco
Journal of Machine Learning Research 14, 3201-3205, 2013
572013
Learning to play no-press diplomacy with best response policy iteration
T Anthony, T Eccles, A Tacchetti, J Kramr, I Gemp, T Hudson, N Porcel, ...
Advances in Neural Information Processing Systems 33, 17987-18003, 2020
402020
Invariant recognition shapes neural representations of visual input
A Tacchetti, L Isik, TA Poggio
Annual review of vision science 4, 403-422, 2018
382018
The computational magic of the ventral stream: sketch of a theory (and why some deep architectures work).
T Poggio, J Mutch, J Leibo, L Rosasco, A Tacchetti
382013
Human-centred mechanism design with Democratic AI
R Koster, J Balaguer, A Tacchetti, A Weinstein, T Zhu, O Hauser, ...
Nature Human Behavior 6, 1398–1407, 2022
362022
Fast, invariant representation for human action in the visual system
L Isik, A Tacchetti, T Poggio
Journal of Neurophysiology 119 (2), 631-640, 2018
362018
A neural architecture for designing truthful and efficient auctions
A Tacchetti, DJ Strouse, M Garnelo, T Graepel, Y Bachrach
arXiv preprint arXiv:1907.05181 3 (3.6), 4, 2019
31*2019
GURLS: a toolbox for large scale multiclass learning
A Tacchetti, P Mallapragada, M Santoro, L Rosasco
NIPS 2011 workshop on parallel and large-scale machine learning. http://cbcl…, 2011
29*2011
Magic materials: a theory of deep hierarchical architectures for learning sensory representations
F Anselmi, JZ Leibo, L Rosasco, J Mutch, A Tacchetti, T Poggio
CBCL paper 16, 2013
242013
Invariant recognition drives neural representations of action sequences
A Tacchetti, L Isik, T Poggio
PLoS computational biology 13 (12), e1005859, 2017
23*2017
Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy
J Kramr, T Eccles, I Gemp, A Tacchetti, KR McKee, M Malinowski, ...
Nature Communications 13 (1), 7214, 2022
222022
The good shepherd: An oracle agent for mechanism design
J Balaguer, R Koster, C Summerfield, A Tacchetti
arXiv preprint arXiv:2202.10135, 2022
142022
D3c: Reducing the price of anarchy in multi-agent learning
I Gemp, KR McKee, R Everett, EA Duez-Guzmn, Y Bachrach, ...
arXiv preprint arXiv:2010.00575, 2020
142020
Regularization by early stopping for online learning algorithms
L Rosasco, A Tacchetti, S Villa
stat 1050, 30, 2014
132014
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
Articoli 1–20