Unsupervised Learning of Invariant Representations in Hierarchical Architectures. - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (CoRR, 2013)

GURLS: a least squares library for supervised learning. - Andrea Tacchetti; Pavan Kumar Mallapragada; Matteo Santoro; Lorenzo Rosasco (J. Mach. Learn. Res., 2013)

Regularization by Early Stopping for Online Learning Algorithms. - Lorenzo Rosasco; Andrea Tacchetti; Silvia Villa (CoRR, 2014)

Unsupervised learning of invariant representations. - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (Theor. Comput. Sci., 2016)

Representation Learning from Orbit Sets for One-Shot Classification. - Andrea Tacchetti; Stephen Voinea; Georgios Evangelopoulos; Tomaso A. Poggio (AAAI Spring Symposia, 2017)

Visual Interaction Networks: Learning a Physics Simulator from Video. - Nicholas Watters; Daniel Zoran; Theophane Weber; Peter W. Battaglia; Razvan Pascanu; Andrea Tacchetti (NIPS, 2017)

Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets. - Andrea Tacchetti; Stephen Voinea; Georgios Evangelopoulos (CoRR, 2017)

Visual Interaction Networks. - Nicholas Watters; Andrea Tacchetti; Theophane Weber; Razvan Pascanu; Peter W. Battaglia; Daniel Zoran (CoRR, 2017)

Invariant recognition drives neural representations of action sequences. - Andrea Tacchetti; Leyla Isik; Tomaso A. Poggio (PLoS Comput. Biol., 2017)

Learning invariant representations of actions and faces. - Andrea Tacchetti (2017)

Trading robust representations for sample complexity through self-supervised visual experience. - Andrea Tacchetti; Stephen Voinea; Georgios Evangelopoulos (NeurIPS, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Forward Models for Multi-Agent Learning. - Andrea Tacchetti; H. Francis Song; Pedro A. M. Mediano; Vinícius Flores Zambaldi; Neil C. Rabinowitz; Thore Graepel; Matthew M. Botvinick; Peter W. Battaglia (CoRR, 2018)

Relational Forward Models for Multi-Agent Learning. - Andrea Tacchetti; H. Francis Song; Pedro A. M. Mediano; Vinícius Flores Zambaldi; János Kramár; Neil C. Rabinowitz; Thore Graepel; Matthew M. Botvinick; Peter W. Battaglia (ICLR (Poster), 2019)

A Neural Architecture for Designing Truthful and Efficient Auctions. - Andrea Tacchetti; DJ Strouse; Marta Garnelo; Thore Graepel; Yoram Bachrach (CoRR, 2019)

Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions. - János Kramár; Neil C. Rabinowitz; Tom Eccles; Andrea Tacchetti (COIN(E)@AAMAS, 2020)

Learning to Play No-Press Diplomacy with Best Response Policy Iteration. - Thomas W. Anthony 001; Tom Eccles; Andrea Tacchetti; János Kramár; Ian Gemp; Thomas C. Hudson; Nicolas Porcel; Marc Lanctot; Julien Pérolat; Richard Everett 001; Satinder Singh 001; Thore Graepel; et al. (NeurIPS, 2020)

Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning. - Justin Fu; Andrea Tacchetti; Julien Pérolat; Yoram Bachrach (J. Artif. Intell. Res., 2021)

D3C: Reducing the Price of Anarchy in Multi-Agent Learning. - Ian Gemp; Kevin R. McKee; Richard Everett 001; Edgar A. Duéñez-Guzmán; Yoram Bachrach; David Balduzzi; Andrea Tacchetti (AAMAS, 2022)

Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. - Ian Gemp; Rahul Savani; Marc Lanctot; Yoram Bachrach; Thomas W. Anthony 001; Richard Everett 001; Andrea Tacchetti; Tom Eccles; János Kramár (AAMAS, 2022)

Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers. - Luke Marris; Ian Gemp; Thomas Anthony 001; Andrea Tacchetti; Siqi Liu 002; Karl Tuyls (NeurIPS, 2022)

Developing, evaluating and scaling learning agents in multi-agent environments. - Ian Gemp; Thomas W. Anthony 001; Yoram Bachrach; Avishkar Bhoopchand; Kalesha Bullard; Jerome T. Connor; Vibhavari Dasagi; Bart De Vylder; Edgar A. Duéñez-Guzmán; Romuald Elie; Richard Everett 001; Daniel Hennes; et al. (AI Commun., 2022)

Human-centered mechanism design with Democratic AI. - Raphael Koster; Jan Balaguer; Andrea Tacchetti; Ari Weinstein; Tina Zhu; Oliver P. Hauser; Duncan Williams; Lucy Campbell-Gillingham; Phoebe Thacker; Matthew M. Botvinick; Christopher Summerfield (CoRR, 2022)

HCMD-zero: Learning Value Aligned Mechanisms from Data. - Jan Balaguer; Raphael Koster; Ari Weinstein; Lucy Campbell-Gillingham; Christopher Summerfield; Matthew M. Botvinick; Andrea Tacchetti (CoRR, 2022)

The Good Shepherd: An Oracle Agent for Mechanism Design. - Jan Balaguer; Raphael Koster; Christopher Summerfield; Andrea Tacchetti (CoRR, 2022)

Scaling Opponent Shaping to High Dimensional Games. - Akbir Khan; Timon Willi; Newton Kwan; Andrea Tacchetti; Chris Lu 001; Edward Grefenstette; Tim Rocktäschel; Jakob N. Foerster (AAMAS, 2024)

Generative Adversarial Equilibrium Solvers. - Denizalp Goktas; David C. Parkes; Ian Gemp; Luke Marris; Georgios Piliouras; Romuald Elie; Guy Lever; Andrea Tacchetti (ICLR, 2024)

Gemma: Open Models Based on Gemini Research and Technology. - Thomas Mesnard; Cassidy Hardin; Robert Dadashi; Surya Bhupatiraju; Shreya Pathak; Laurent Sifre; Morgane Rivière; Mihir Sanjay Kale; Juliette Love; Pouya Tafti; Léonard Hussenot; Aakanksha Chowdhery; et al. (CoRR, 2024)

Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem. - Raphael Koster; Miruna Pîslar; Andrea Tacchetti; Jan Balaguer; Leqi Liu; Romuald Elie; Oliver P. Hauser; Karl Tuyls; Matt M. Botvinick; Christopher Summerfield (CoRR, 2024)

Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience. - Manfred Diaz; Liam Paull; Andrea Tacchetti (Trans. Mach. Learn. Res., 2024)

Teamwork Reinforcement Learning With Concave Utilities. - Zheng Yu; Junyu Zhang; Zheng Wen; Andrea Tacchetti; Mengdi Wang; Ian Gemp (IEEE Trans. Mob. Comput., 2024)

Language Agents as Digital Representatives in Collective Decision-Making. - Daniel Jarrett; Miruna Pîslar; Michiel A. Bakker; Michael Henry Tessler; Raphael Köster; Jan Balaguer; Romuald Elie; Christopher Summerfield; Andrea Tacchetti (CoRR, 2025)