2026
  • Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training
    Y. Mroueh, N. Dupuis, B. Belgodere, A. Nitsure, M. Rigotti, K. Greenewald, J. Navratil, J. Ross, J. Rios
    International Conference on Learning Representations, ICLR 2026
    • 2025
  • Eliciting Reasoning in Language Models with Cognitive Tools
    B. Ebouky, A. Bartezzaghi, M. Rigotti
    Advances in Neural Information Processing Systems 39, NeurIPS 2025
  • Factorized embedding of goal and uncertainty in the lateral prefrontal cortex guides stably flexible learning
    Y. Sung, M. Rigotti, S.W. Lee
    Nature Communications, 26 Nov 2025
  • Detection and Simulation of Urban Heat Islands Using a Fine-Tuned Geospatial Foundation Model for Microclimate Impact Prediction
    J. Fleckenstein, D. Kreismann, T.R. Govindasamy, T. Brunschwiler, E. Vos, M. Rigotti
    Advances in Neural Information Processing Systems 39, Workshop: Tackling Climate Change with Machine Learning 2025
  • Factorized Prefrontal Geometry of Goal and Uncertainty Explains Flexible yet Stable Human Goal Pursuit
    Y. Sung, M. Rigotti, S.W. Lee
    Advances in Neural Information Processing Systems 39, Workshop on Symmetry and Geometry in Neural Representations 2025
  • Q-SAM2: Accurate Quantization for Segment Anything Model 2
    N. Farronato, F. Scheidegger, M. Rigotti, C. Malossi, M. Magno, H. Qin
    arXiv preprint, arXiv:2506.09782 2025
  • Show or Tell? Effectively prompting Vision-Language Models for semantic segmentation
    N. Avogaro, T. Frick, M. Rigotti, A. Bartezzaghi, F. Janicki, A.C.I. Malossi, K. Schindler, R. Assaf
    Transactions on Machine Learning Research, TMLR 2025
  • VP Lab: a PEFT-Enabled Visual Prompting Laboratory for Semantic Segmentation
    N. Avogaro, T. Frick, Y.G. Cinar, D. Caraballo, C. Skura, F.M. Janicki, P. Kluska, B. Ebouky, N. Farronato, F. Scheidegger, C. Malossi, K. Schindler, A. Bartezzaghi, R. Assaf, M. Rigotti
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, Demo Track, CVPR 2025
  • Towards Reliable Conversational Data Analytics
    S. Amer-Yahia, J. Bogojeska, R. Facchinetti, V. Franceschi, A. Gionis, K. Hose, G. Koutrika, R. Kouyos, M. Lissandrini, S. Maniu, K. Mirylenka, D. Mottin, T. Palpanas, M. Rigotti, Y. Velegrakis
    International Conference on Extending Database Technology, EDBT 2025
    • 2024
  • Distributional Preference Alignment of LLMs via Optimal Transport
    I. Melnyk, Y. Mroueh, B. Belgodere, M. Rigotti, A. Nitsure, M. Yurochkin, K. Greenewald, J. Navratil, J. Ross
    Advances in Neural Information Processing Systems 38, NeurIPS 2024
  • Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
    G. Rioux, A. Nitsure, M. Rigotti, K. Greenewald, Y. Mroueh
    Advances in Neural Information Processing Systems 38, NeurIPS 2024
  • Auditing and Generating Synthetic Data with Controllable Trust Trade-offs
    B. Belgodere, P. Dognin, A. Ivankay, I. Melnyk, Y. Mroueh, A. Mojsilovic, J. Navartil, A. Nitsure, I. Padhi, M. Rigotti, J. Ross, Y. Schiff, R. Vedpathak, R.A. Young
    IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2024
  • Probabilistic Feature Matching for Fast Scalable Visual Prompting
    T. Frick, C. Skura, F.M. Janicki, R. Assaf, N. Avogaro, D. Caraballo-Rivera, Y.G. Cinar, B. Ebouky, I. Giurgiu, T. Katsuki, P.S. Kluska, C. Malossi, H. Qiu, T. Sakai, F. Scheidegger, A. Simeski, D. Yang, A. Bartezzaghi, M. Rigotti
    Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI 2024
  • Interactive Image Segmentation Guided by Visual Prompting
    T. Frick, C. Skura, F.M. Janicki, R. Assaf, N. Avogaro, D. Caraballo-Rivera, Y.G. Cinar, B. Ebouky, I. Giurgiu, T. Katsuki, P.S. Kluska, C. Malossi, H. Qiu, T. Sakai, F. Scheidegger, A. Simeski, D. Yang, A. Bartezzaghi, M. Rigotti
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, Demo Track, CVPR 2024
  • Risk Aware Benchmarking of Large Language Models
    A. Nitsure, Y. Mroueh, M. Rigotti, K. Greenewald, B. Belgodere, M. Yurochkin, J. Navratil, I. Melnyk, J. Ross
    International Conference on Machine Learning, ICML 2024
  • Mixed selectivity: Cellular computations for complexity
    K.M. Tye, E.K. Miller, F.H. Taschbach, M.K. Benna, M. Rigotti, S. Fusi
    Neuron, 112, July 17, 2024
  • Adaptive Conformal Regression with Jackknife+ Rescaled Scores
    N. Deutschmann, M. Rigotti, M. Rodriguez Martinez
    Transactions on Machine Learning Research, TMLR 2024
  • MC Layer Normalization for calibrated uncertainty in Deep Learning
    T. Frick, D. Antognini, I. Giurgiu, B.F. Grewe, C. Malossi, R.J.B. Zhu, M. Rigotti
    Transactions on Machine Learning Research, TMLR 2024
  • On the generalization capacity of neural networks during generic multimodal reasoning
    T. Ito, S. Dan, M. Rigotti, J. Kozloski, M. Campbell
    International Conference on Learning Representations, ICLR 2024
  • Unraveling the Key Components of OOD Generalization via Diversification
    H. Benoit, L. Jiang, A. Atanov, O. Fatih Kar, M. Rigotti, A. Zamir
    International Conference on Learning Representations, ICLR 2024
  • AI for bridge inspection with IBM Inspecto
    A.C.I. Malossi, R. Assaf, N. Avogaro, A. Bartezzaghi, B. Ebouky, T. Frick, I. Giurgiu, F.M. Janicki, P. Kluska, M. Rigotti, F. Scheidegger, A. Simeski, C. Skura, D. Caraballo, Y. Cinar, F. Bormlund, S. Gjerding
    IABMAS, 2024
    • 2023
  • Risk Assessment and Statistical Significance in the Age of Foundation Models
    A. Nitsure, Y. Mroueh, M. Rigotti, K. Greenewald, B. Belgodere, M. Yurochkin, J. Navratil, I. Melnyk, J. Ross
    NeurIPS, Socially Responsible Language Modelling Research Workshop (SoLaR) 2023
  • DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications
    A. Ivankay, M. Rigotti, P. Frossard
    The 61st Annual Meeting of the Association for Computational Linguistics, ACL (Awarded an oral presentation) 2023
  • Towards Workflows for the Use of AI Foundation Models in Visual Inspection Applications
    M. Rigotti, D. Antognini, R. Assaf, K. Bakirci, T. Frick, I. Giurgiu, K. Janoušková, F. Janicki, H. Jubran, C. Malossi, A. Meterez, F. Scheidegger
    ce/papers, 6(5), pp.605-613, 2023
  • Importance of Digitalization and Standardization for Bridge and Tunnel Monitoring and Predictive Maintenance
    M. Weise, Mi. Böhms, D. Allaix, A. Sanchez-Rodriguez, M. Rigotti
    ce/papers, 6(5), pp.592-599, 2023
  • Risk Assessment and Statistical Significance in the Age of Foundation Models
    A. Nitsure, Y. Mroueh, M. Rigotti, K. Greenewald, B. Belgodere, M. Yurochkin, J. Navratil, I. Melnyk, J. Ross
    arXiv preprint, arXiv:2310.07132, 2023
    • 2022
  • Cloud-Based Real-Time Molecular Screening Platform with MolFormer
    B. Belgodere, V. Chenthamarakshan, P. Das, P. Dognin, T. Kurien, I. Melnyk, Y. Mroueh, I. Padhi, M. Rigotti, J. Ross, Y. Schiff, R.A. Young
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD Demo 2022
  • Compositional generalization through abstract representations in human and artificial neural networks
    T. Ito, T. Klinger, D.H. Schultz, J.D. Murray, M.W. Cole, M. Rigotti
    Advances in Neural Information Processing Systems 36, NeurIPS (Awarded an oral presentation) 2022
  • The implications of categorical and category-free mixed selectivity on representational geometries
    M.T. Kaufman, M.K. Benna, M. Rigotti, F. Stefanini, S. Fusi, A.K. Churchland
    Current Opinion in Neurobiology, 77:102644, 2022
  • Attention-based Interpretability with Concept Transformers
    M. Rigotti, C. Miksovic, I. Giurgiu, T. Gschwind, P. Scotton
    International Conference on Learning Representations, ICLR 2022
  • Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures
    K. Janouskova, M. Rigotti, I. Giurgiu, C. Malossi
    European Conference on Computer Vision, CVCIE Workshop @ ECCV (Awarded best paper award) 2022
  • Active Learning for Imbalanced Civil Infrastructure Data
    T. Frick, D. Antognini, M. Rigotti, I. Giurgiu, B. Grewe, C. Malossi
    European Conference on Computer Vision, CVCIE Workshop @ ECCV 2022
  • Design of a Cloud-Based Data Platform for Standardized Machine Learning Workflows with Applications to Transport Infrastructure
    A. Bartezzaghi, I. Giurgiu, C. Marchiori, M. Rigotti, R. Sebastian, C. Malossi
    IEEE 21st Mediterranean Electrotechnical Conference, MELECON 2022
  • 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, R.A. Young, B. Belgodere
    Journal of Artificial Intelligence Research, 73, 437-459, 2022
    • 2021
  • 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: 1417, 2021
  • Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
    R. Zhu, M. Rigotti
    Advances in Neural Information Processing Systems 35, NeurIPS 2021
  • Self-correcting Q-learning
    R. Zhu, M. Rigotti
    Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021
  • Tabular Transformers for Modeling Multivariate Time Series
    I. Padhi, Y. Schiff, I. Melnyk, M. Rigotti, Y. Mroueh, P. Dognin, J. Ross, R. Nair, E. Altman
    IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021
    • 2020
  • The Geometry of Abstraction in the Hippocampus and Prefrontal Cortex
    S. Bernardi, M.K. Benna, M. Rigotti, J. Munuera, S. Fusi, C.D. Salzman
    Cell, 183, 1-14, 2020
  • Unbalanced Sobolev Descent
    Y. Mroueh, M. Rigotti
    Advances in Neural Information Processing Systems 34, NeurIPS 2020
  • Alleviating Noisy Data in Image Captioning with Cooperative Distillation
    P. Dognin, I. Melnyk, Y. Mroueh, I. Padhi, M. Rigotti, J. Ross, Y. Schiff
    Computer Vision and Pattern Recognition Conference (CVPR 2020), VizWiz Grand Challenge Workshop 2020
    • 2019
  • Sobolev Independence Criterion
    Y. Mroueh, T. Sercu, M. Rigotti, I. Padhi, C. Dos Santos
    Advances in Neural Information Processing Systems 33, NeurIPS 2019
  • RAPA-ConvNets: Modified Convolutional Networks for Accelerated Training on Architectures with Analog Arrays
    M.J. Rasch, T. Gokmen, M. Rigotti, W. Haensch
    Frontiers in Neuroscience | Neuromorphic Engineering, 13:753, 2019
  • Measuring prefrontal representational geometry: fMRI adaptation vs pattern analysis
    A. Bhandari, M.K. Benna, M. Rigotti, S. Fusi, D. Badre
    Conference on Cognitive Computational Neuroscience, CCN 2019
  • Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
    A. Choromanska, B. Cowen, S. Kumaravel, R. Luss, M. Rigotti, I. Rish, B. Kingsbury, P. DiAchille, V. Gurev, R. Tejwani, D. Bouneffouf
    International Conference on Machine Learning, ICML 2019
  • The geometry of abstraction in hippocampus and pre-frontal cortex
    S. Bernardi, M.K. Benna, M. Rigotti, J. Munuera, S. Fusi, C.D. Salzman
    Computational and Systems Neuroscience Conference, CoSyNe 2019
  • Signatures of low-dimensional neural predictive manifolds
    S. Recanatesi, M. Farrell, G. Lajoie, S. Deneve, M. Rigotti, E. Shea-Brown
    Computational and Systems Neuroscience Conference, CoSyNe 2019
  • Signatures and mechanisms of low-dimensional neural predictive manifolds
    S. Recanatesi, M. Farrell, G. Lajoie, S. Deneve, M. Rigotti, E. Shea-Brown
    bioRxiv, 471987, 2019
    • 2018
  • Efficient ConvNets for Analog Arrays
    M.J. Rasch, T. Gokmen, M. Rigotti, W. Haensch
    arXiv, 1807.01356, 2018
  • Shared neural coding for social hierarchy and reward value in primate amygdala
    J. Munuera, M. Rigotti, C.D. Salzman
    Nature Neuroscience, 21: 415-423, 2018
    • 2017
  • Hebbian Learning in a Random Network Captures Selectivity Properties of Prefrontal Cortex
    G.W. Lindsay, M. Rigotti, M.R. Warden, E.K. Miller, S. Fusi
    Journal of Neuroscience, 37:11021-11036, 2017
  • Neurophysiological mechanisms supporting flexible, context specific, emotional regulation
    S. Bernardi, J. Munuera, M. Rigotti, S. Fusi, and C.D. Salzman
    Biological Psychiatry, volume 81, pages S272, 2017
  • The hippocampus as a predictive recurrent neural network
    S. Recanatesi, G. Wayne, M. Rigotti
    Computational and Systems Neuroscience Conference, CoSyNe 2017
    • 2016
  • Energy-Efficient Neuromorphic Classifiers
    D. Martí, M. Rigotti, M. Seok, S. Fusi
    Neural Computation, 28: 2011-2044, 2016
  • Why neurons mix: high dimensionality for higher cognition
    S. Fusi, E.K. Miller, M. Rigotti
    Current Opinion in Neurobiology, 37: 66-74, 2016
    • 2015
  • Hippocampal-prefrontal input supports spatial encoding in working memory
    T. Spellman, M. Rigotti, S.E. Ahmari, S. Fusi, J.A. Gogos, J.A. Gordon
    Nature, 522:309-314, 2015
  • Abstract context representations in primate amygdala and prefrontal cortex
    A. Saez, M. Rigotti, S. Ostojic, S. Fusi, C.D. Salzman
    Neuron,, 87:869-881 2015
  • Estimating the dimensionality of neural responses with fMRI Repetition Suppression
    M. Rigotti, S. Fusi
    Advances in Neural Information Processing Systems 28, MLINI Workshop at NIPS 2015
  • Neurophysiological mechanisms supporting flexible, context specific, emotional regulation
    S. Bernardi, J. Munuera, M. Rigotti, S. Fusi, and C.D. Salzman
    Biological Psychiatry, volume 77, pages 136S-136S, 2015
    • 2014
  • Hebbian-inspired rewiring of a random network replicates pattern of selectivity seen in PFC
    G. Lindsay, M. Rigotti, M. R. Warden, E. K. Miller, S. Fusi
    BMC Neuroscience, 15 (Suppl 1):P160, 2014
    • 2013
  • The importance of mixed selectivity in complex cognitive tasks
    M. Rigotti, O. Barak, M.R. Warden, X.-J. Wang, N.D. Daw, E.K. Miller, S. Fusi
    Nature, 497:585-590, 2013
  • The sparseness of mixed selectivity neurons controls the generalization-discrimination trade-off
    O. Barak, M. Rigotti, S. Fusi
    Journal of Neuroscience, 33:3844-56, 2013
  • Scalability properties of multimodular networks with dynamic gating
    D. Marti, O. Barak, M. Rigotti, S. Fusi
    BMC Neuroscience, 14(Suppl 1):P136, 2013
  • A VLSI chip with spike-based synaptic plasticity for online learning in real-time
    F. Stefanini, M. Rigotti, S. Fusi and G. Indiveri
    International Workshop on Neuromorphic and Brain-Based Computing Systems, NeuComp (Grenoble, France) 2013
  • Scalability properties of multimodular networks with dynamic gating
    D. Marti, O. Barak, M. Rigotti and S. Fusi
    Computational and Systems Neuroscience Conference, CoSyNe 2013
    • 2012
  • An adaptive spiking neural network for decision making in partially observable environments
    M. Rigotti, D. Ben Dayan Rubin, N.D. Daw and S. Fusi
    Cosyne: Computational and Systems Neuroscience Conference, CoSyNe 2012
  • Neural representations that are good for both generalization and discrimination
    O. Barak, M. Rigotti, S. Fusi
    Computational and Systems Neuroscience Conference, CoSyNe 2012
    • 2011
  • A simple derivation of a bound on the Perceptron margin using Singular Value Decomposition
    O. Barak, M. Rigotti
    Neural Computation, 23:1935-43, 2011
  • Context, correlation and decorrelation with randomly connected neurons
    O. Barak, M. Rigotti and S. Fusi
    Computational and Systems Neuroscience Conference, CoSyNe 2011
    • 2010
  • Internal representation of task rules by recurrent dynamics: the importance of the diversity of neural responses
    M. Rigotti, D. Ben Dayan Rubin, X.-J. Wang and S. Fusi
    Frontiers in Computational Neuroscience, 4:24, 2010
  • Attractor concretion as a mechanism for the formation of context representations
    M. Rigotti, D. Ben Dayan Rubin, S.E. Morrison, C.D. Salzman and S. Fusi
    NeuroImage, 52:833-47, 2010
    • 2009
  • Power-law autocorrelation of neural activity in models of mental states that are hierarchically organized
    F. Chersi, M. Rigotti and S. Fusi
    BMC Neurosciencee, 10(Suppl 1):P292, 2009
    • 2007
  • Event-driven transitions between attractors in spiking networks
    M. Mattia, M. Rigotti and S. Fusi
    Computational and Systems Neuroscience Conference, CoSyNe 2007
    • 2005
  • An H-theorem for the general relativistic Ornstein-Uhlenbeck process
    M. Rigotti and F. Debbasch
    Journal of Mathematical Physics, 46:103303, 2005