Mattia Rigotti
Mattia Rigotti
Researcher at IBM Research AI
Verified email at - Homepage
Cited by
Cited by
The importance of mixed selectivity in complex cognitive tasks
M Rigotti, O Barak, MR Warden, XJ Wang, ND Daw, EK Miller, S Fusi
Nature 497 (7451), 585-590, 2013
Hippocampal–prefrontal input supports spatial encoding in working memory
T Spellman, M Rigotti, SE Ahmari, S Fusi, JA Gogos, JA Gordon
Nature 522 (7556), 309-314, 2015
Why neurons mix: high dimensionality for higher cognition
S Fusi, EK Miller, M Rigotti
Current opinion in neurobiology 37, 66-74, 2016
The geometry of abstraction in hippocampus and prefrontal cortex
S Bernardi, MK Benna, M Rigotti, J Munuera, S Fusi, D Salzman
The sparseness of mixed selectivity neurons controls the generalization–discrimination trade-off
O Barak, M Rigotti, S Fusi
Journal of Neuroscience 33 (9), 3844-3856, 2013
Internal representation of task rules by recurrent dynamics: The importance of the diversity of neural responses
M Rigotti, DBD Rubin, XJ Wang, S Fusi
Frontiers in Computational Neuroscience 4, 24-29, 2010
Abstract context representations in primate amygdala and prefrontal cortex
A Saez, M Rigotti, S Ostojic, S Fusi, CD Salzman
Neuron 87 (4), 869-881, 2015
Shared neural coding for social hierarchy and reward value in primate amygdala
J Munuera, M Rigotti, CD Salzman
Nature neuroscience 21 (3), 415-423, 2018
Tabular transformers for modeling multivariate time series
I Padhi, Y Schiff, I Melnyk, M Rigotti, Y Mroueh, P Dognin, J Ross, R Nair, ...
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
A Choromanska, B Cowen, S Kumaravel, R Luss, M Rigotti, I Rish, ...
International Conference on Machine Learning 97, 1193-1202, 2019
Predictive learning as a network mechanism for extracting low-dimensional latent space representations
S Recanatesi, M Farrell, G Lajoie, S Deneve, M Rigotti, E Shea-Brown
Nature communications 12 (1), 1417, 2021
Attractor concretion as a mechanism for the formation of context representations
M Rigotti, D Ben Dayan Rubin, SE Morrison, CD Salzman, S Fusi
Neuroimage 52 (3), 833-847, 2010
Attention-based interpretability with concept transformers
M Rigotti, C Miksovic, I Giurgiu, T Gschwind, P Scotton
International conference on learning representations, 2021
Hebbian learning in a random network captures selectivity properties of the prefrontal cortex
GW Lindsay, M Rigotti, MR Warden, EK Miller, S Fusi
Journal of Neuroscience 37 (45), 11021-11036, 2017
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge
P Dognin, I Melnyk, Y Mroueh, I Padhi, M Rigotti, J Ross, Y Schiff, ...
Journal of Artificial Intelligence Research 73, 437-459, 2022
Energy-efficient neuromorphic classifiers
D Marti, M Rigotti, M Seok, S Fusi
Neural computation 28 (10), 2011-2044, 2016
Ben Dayan Rubin D, Wang XJ, Fusi S
M Rigotti
Internal representation of task rules by recurrent dynamics: the importance …, 2010
Compositional generalization through abstract representations in human and artificial neural networks
T Ito, T Klinger, D Schultz, J Murray, M Cole, M Rigotti
Advances in neural information processing systems 35, 32225-32239, 2022
The implications of categorical and category-free mixed selectivity on representational geometries
MT Kaufman, MK Benna, M Rigotti, F Stefanini, S Fusi, AK Churchland
Current opinion in neurobiology 77, 102644, 2022
Self-correcting Q-Learning
R Zhu, M Rigotti
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 11185 …, 2020
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