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ORCIDMattia Rigotti
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2020 – today
- 2024
[j8]Nicolas Deutschmann, Mattia Rigotti, María Rodríguez Martínez:
Adaptive Conformal Regression with Split-Jackknife+ Scores. Trans. Mach. Learn. Res. 2024 (2024)- [j7]Thomas Frick, Diego Antognini, Ioana Giurgiu, Benjamin F. Grewe, Cristiano Malossi, Rong J. B. Zhu, Mattia Rigotti:
MC Layer Normalization for calibrated uncertainty in Deep Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c16]Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar, Mattia Rigotti, Amir Zamir:
Unraveling the Key Components of OOD Generalization via Diversification. ICLR 2024 - [c15]Takuya Ito, Soham Dan, Mattia Rigotti, James R. Kozloski, Murray Campbell:
On the generalization capacity of neural networks during generic multimodal reasoning. ICLR 2024 - [c14]Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jarret Ross:
Risk Aware Benchmarking of Large Language Models. ICML 2024 - [c13]Thomas Frick, Cezary Skura, Filip Janicki, Roy Assaf, Niccolo Avogaro, Daniel Caraballo, Yagmur Gizem Cinar, Brown Ebouky, Ioana Giurgiu, Takayuki Katsuki, Piotr Kluska, Cristiano Malossi, Haoxiang Qiu, Tomoya Sakai, Florian Scheidegger, Andrej Simeski, Daniel Yang, Andrea Bartezzaghi, Mattia Rigotti:
Probabilistic Feature Matching for Fast Scalable Visual Prompting. IJCAI 2024: 8648-8652 - [i22]Takuya Ito, Soham Dan, Mattia Rigotti, James R. Kozloski, Murray Campbell:
On the generalization capacity of neural networks during generic multimodal reasoning. CoRR abs/2401.15030 (2024) - [i21]Markus Pobitzer, Filip Janicki, Mattia Rigotti, Cristiano Malossi:
Outline-Guided Object Inpainting with Diffusion Models. CoRR abs/2402.16421 (2024) - [i20]Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross:
Distributional Preference Alignment of LLMs via Optimal Transport. CoRR abs/2406.05882 (2024) - [i19]Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh:
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking. CoRR abs/2406.06425 (2024) - 2023
- [c12]Adam Ivankay, Mattia Rigotti, Pascal Frossard:
DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications. ACL (1) 2023: 11499-11533 - [i18]Brian Belgodere, Pierre L. Dognin, Adam Ivankay, Igor Melnyk, Youssef Mroueh, Aleksandra Mojsilovic, Jirí Navrátil, Apoorva Nitsure, Inkit Padhi, Mattia Rigotti, Jerret Ross, Yair Schiff, Radhika Vedpathak, Richard A. Young:
Auditing and Generating Synthetic Data with Controllable Trust Trade-offs. CoRR abs/2304.10819 (2023) - [i17]Nicolas Deutschmann, Mattia Rigotti, María Rodríguez Martínez:
Adaptive Conformal Regression with Jackknife+ Rescaled Scores. CoRR abs/2305.19901 (2023) - [i16]Adam Ivankay, Mattia Rigotti, Pascal Frossard:
DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications. CoRR abs/2307.02094 (2023) - [i15]Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross:
Risk Assessment and Statistical Significance in the Age of Foundation Models. CoRR abs/2310.07132 (2023) - [i14]Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar
, Mattia Rigotti, Amir Zamir:
Unraveling the Key Components of OOD Generalization via Diversification. CoRR abs/2312.16313 (2023) - 2022
- [j6]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young, Brian Belgodere:
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. J. Artif. Intell. Res. 73: 437-459 (2022) - [c11]Klára Janousková, Mattia Rigotti, Ioana Giurgiu, Cristiano Malossi:
Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures. ECCV Workshops (7) 2022: 244-257 - [c10]Thomas Frick, Diego Antognini, Mattia Rigotti, Ioana Giurgiu, Benjamin F. Grewe, Cristiano Malossi:
Active Learning for Imbalanced Civil Infrastructure Data. ECCV Workshops (7) 2022: 283-298 - [c9]Mattia Rigotti, Christoph Miksovic, Ioana Giurgiu, Thomas Gschwind, Paolo Scotton:
Attention-based Interpretability with Concept Transformers. ICLR 2022 - [c8]Takuya Ito, Tim Klinger, Douglas Schultz, John Murray, Michael W. Cole, Mattia Rigotti:
Compositional generalization through abstract representations in human and artificial neural networks. NeurIPS 2022 - [c7]Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young:
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. ECML/PKDD (6) 2022: 641-644 - [i13]Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young:
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. CoRR abs/2208.06665 (2022) - [i12]Klára Janousková, Mattia Rigotti, Ioana Giurgiu, Cristiano Malossi:
Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures. CoRR abs/2209.11159 (2022) - [i11]Thomas Frick, Diego Antognini, Mattia Rigotti, Ioana Giurgiu, Benjamin F. Grewe, Cristiano Malossi:
Active Learning for Imbalanced Civil Infrastructure Data. CoRR abs/2210.10586 (2022) - [i10]Adam Ivankay, Mattia Rigotti, Ivan Girardi, Chiara Marchiori, Pascal Frossard:
Estimating the Adversarial Robustness of Attributions in Text with Transformers. CoRR abs/2212.09155 (2022) - 2021
- [c6]Rong Zhu, Mattia Rigotti:
Self-correcting Q-learning. AAAI 2021: 11185-11192 - [c5]Inkit Padhi, Yair Schiff, Igor Melnyk, Mattia Rigotti, Youssef Mroueh, Pierre L. Dognin, Jerret Ross, Ravi Nair, Erik R. Altman:
Tabular Transformers for Modeling Multivariate Time Series. ICASSP 2021: 3565-3569 - [c4]Rong Zhu, Mattia Rigotti:
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks. NeurIPS 2021: 17592-17603 - [i9]Mattia Rigotti, Rong Zhu:
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks. CoRR abs/2105.04683 (2021) - 2020
- [c3]Youssef Mroueh, Mattia Rigotti:
Unbalanced Sobolev Descent. NeurIPS 2020 - [i8]Youssef Mroueh, Mattia Rigotti:
Unbalanced Sobolev Descent. CoRR abs/2009.14148 (2020) - [i7]Inkit Padhi, Yair Schiff, Igor Melnyk, Mattia Rigotti, Youssef Mroueh, Pierre L. Dognin, Jerret Ross, Ravi Nair, Erik R. Altman:
Tabular Transformers for Modeling Multivariate Time Series. CoRR abs/2011.01843 (2020) - [i6]Rong Zhu, Mattia Rigotti:
Self-correcting Q-Learning. CoRR abs/2012.01100 (2020) - [i5]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff:
Alleviating Noisy Data in Image Captioning with Cooperative Distillation. CoRR abs/2012.11691 (2020) - [i4]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young, Brian Belgodere:
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. CoRR abs/2012.11696 (2020)
2010 – 2019
- 2019
- [c2]Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf:
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. ICML 2019: 1193-1202 - [c1]Youssef Mroueh, Tom Sercu, Mattia Rigotti, Inkit Padhi, Cícero Nogueira dos Santos:
Sobolev Independence Criterion. NeurIPS 2019: 9505-9515 - [i3]Youssef Mroueh, Tom Sercu, Mattia Rigotti, Inkit Padhi, Cícero Nogueira dos Santos:
Sobolev Independence Criterion. CoRR abs/1910.14212 (2019) - 2018
- [i2]Malte J. Rasch, Tayfun Gokmen, Mattia Rigotti, Wilfried Haensch:
Efficient ConvNets for Analog Arrays. CoRR abs/1807.01356 (2018) - 2016
- [j5]Daniel Martí, Mattia Rigotti, Mingoo Seok, Stefano Fusi:
Energy-Efficient Neuromorphic Classifiers. Neural Comput. 28(10): 2011-2044 (2016) - 2015
- [i1]Daniel Martí, Mattia Rigotti, Mingoo Seok, Stefano Fusi:
Energy-efficient neuromorphic classifiers. CoRR abs/1507.00235 (2015) - 2013
- [j4]Mattia Rigotti, Omri Barak, Melissa R. Warden, Xiao-Jing Wang, Nathaniel D. Daw, Earl K. Miller, Stefano Fusi:
The importance of mixed selectivity in complex cognitive tasks. Nat. 497(7451): 585-590 (2013) - 2011
- [j3]Omri Barak, Mattia Rigotti:
A Simple Derivation of a Bound on the Perceptron Margin Using Singular Value Decomposition. Neural Comput. 23(8): 1935-1943 (2011) - 2010
- [j2]Mattia Rigotti, Daniel Ben Dayan Rubin, Xiao-Jing Wang, Stefano Fusi:
Internal Representation of Task Rules by Recurrent Dynamics: The Importance of the Diversity of Neural Responses. Frontiers Comput. Neurosci. 4: 24 (2010) - [j1]Mattia Rigotti, Daniel Ben Dayan Rubin, Sara E. Morrison, C. Daniel Salzman, Stefano Fusi:
Attractor concretion as a mechanism for the formation of context representations. NeuroImage 52(3): 833-847 (2010)
Coauthor Index
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last updated on 2024-10-21 21:33 CEST by the dblp team
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