Cadherin-Dependent Cell Morphology in an Epithelium: Constructing a Quantitative Dynamical Model. - Ian M. Gemp; Richard W. Carthew; Sascha Hilgenfeldt (PLoS Comput. Biol., 2011)

Modeling Context in Cognition Using Variational Inequalities. - Ian Gemp; Sridhar Mahadevan (AAAI Fall Symposia, 2014)

Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces. - Sridhar Mahadevan; Bo Liu 006; Philip S. Thomas; William Dabney; Stephen Giguere 001; Nicholas Jacek; Ian Gemp; Ji Liu 002 (CoRR, 2014)

Solving Large Sustainable Supply Chain Networks Using Variational Inequalities. - Ian Gemp; Sridhar Mahadevan; Bo Liu 006 (AAAI Workshop: Computational Sustainability, 2015)

Deep Generative Models for Spectroscopic Analysis on Mars. - Ian Gemp; Ishan P. Durugkar; Mario Parente; Melinda Darby Dyar; Sridhar Mahadevan (CoRR, 2016)

Online Monotone Optimization. - Ian Gemp; Sridhar Mahadevan (CoRR, 2016)

Automated Data Cleansing through Meta-Learning. - Ian Gemp; Georgios Theocharous; Mohammad Ghavamzadeh (AAAI, 2017)

Generative Multi-Adversarial Networks. - Ishan P. Durugkar; Ian Gemp; Sridhar Mahadevan (ICLR (Poster), 2017)

Unmixing in the presence of nuisances with deep generative models. - Mario Parente; Ian Gemp; Ishan P. Durugkar (IGARSS, 2017)

Online Monotone Games. - Ian Gemp; Sridhar Mahadevan (CoRR, 2017)

Global Convergence to the Equilibrium of GANs using Variational Inequalities. - Ian Gemp; Sridhar Mahadevan (CoRR, 2018)

Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. - Bo Liu 006; Ian Gemp; Mohammad Ghavamzadeh; Ji Liu 002; Sridhar Mahadevan; Marek Petrik (J. Artif. Intell. Res., 2018)

Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. - Kevin R. McKee; Ian Gemp; Brian McWilliams; Edgar A. Duéñez-Guzmán; Edward Hughes 001; Joel Z. Leibo (AAMAS, 2020)

Smooth markets: A basic mechanism for organizing gradient-based learners. - David Balduzzi; Wojciech M. Czarnecki; Tom Anthony 001; Ian Gemp; Edward Hughes 001; Joel Z. Leibo; Georgios Piliouras; Thore Graepel (ICLR, 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)

EigenGame: PCA as a Nash Equilibrium. - Ian Gemp; Brian McWilliams; Claire Vernade; Thore Graepel (ICLR, 2021)

A Neural Network Auction For Group Decision Making Over a Continuous Space. - Yoram Bachrach; Ian Gemp; Marta Garnelo; János Kramár; Tom Eccles; Dan Rosenbaum; Thore Graepel (IJCAI, 2021)

Game-theoretic Vocabulary Selection via the Shapley Value and Banzhaf Index. - Roma Patel; Marta Garnelo; Ian Gemp; Chris Dyer; Yoram Bachrach (NAACL-HLT, 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)

EigenGame Unloaded: When playing games is better than optimizing. - Ian Gemp; Brian McWilliams; Claire Vernade; Thore Graepel (ICLR, 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)

Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering. - Elise van der Pol; Ian Gemp; Yoram Bachrach (TAG-ML, 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)

The Generalized Eigenvalue Problem as a Nash Equilibrium. - Ian Gemp; Charlie Chen; Brian McWilliams (CoRR, 2022)

Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering. - Elise van der Pol; Ian Gemp; Yoram Bachrach; Richard Everett 001 (CoRR, 2022)

Game Theoretic Rating in N-player general-sum games with Equilibria. - Luke Marris; Marc Lanctot; Ian Gemp; Shayegan Omidshafiei; Stephen McAleer; Jerome T. Connor; Karl Tuyls; Thore Graepel (CoRR, 2022)

AlphaSnake: Policy Iteration on a Nondeterministic NP-hard Markov Decision Process. - Kevin Du; Ian Gemp; Yi Wu 013; Yingying Wu (CoRR, 2022)

AlphaSnake: Policy Iteration on a Nondeterministic NP-Hard Markov Decision Process (Student Abstract). - Kevin Du; Ian Gemp; Yi Wu 013; Yingying Wu (AAAI, 2023)

Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games. - Zun Li 002; Marc Lanctot; Kevin R. McKee; Luke Marris; Ian Gemp; Daniel Hennes; Kate Larson; Yoram Bachrach; Michael P. Wellman; Paul Muller (AAMAS, 2023)

The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium. - Ian Gemp; Charlie Chen; Brian McWilliams (ICLR, 2023)

Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples. - Marco Jiralerspong; Avishek Joey Bose; Ian Gemp; Chongli Qin; Yoram Bachrach; Gauthier Gidel (NeurIPS, 2023)

Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning. - Zun Li 002; Marc Lanctot; Kevin R. McKee; Luke Marris; Ian Gemp; Daniel Hennes; Paul Muller; Kate Larson; Yoram Bachrach; Michael P. Wellman (CoRR, 2023)

Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×2 Normal-Form Games. - Luke Marris; Ian Gemp; Georgios Piliouras (CoRR, 2023)

Approximating the Core via Iterative Coalition Sampling. - Ian Gemp; Marc Lanctot; Luke Marris; Yiran Mao; Edgar A. Duéñez-Guzmán; Sarah Perrin; András György 001; Romuald Elie; Georgios Piliouras; Michael Kaisers; Daniel Hennes; Kalesha Bullard; et al. (AAMAS, 2024)

NfgTransformer: Equivariant Representation Learning for Normal-form Games. - Siqi Liu 002; Luke Marris; Georgios Piliouras; Ian Gemp; Nicolas Heess (ICLR, 2024)

Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization. - Ian Gemp; Luke Marris; Georgios Piliouras (ICLR, 2024)

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

States as Strings as Strategies: Steering Language Models with Game-Theoretic Solvers. - Ian Gemp; Yoram Bachrach; Marc Lanctot; Roma Patel; Vibhavari Dasagi; Luke Marris; Georgios Piliouras; Siqi Liu 002; Karl Tuyls (CoRR, 2024)

Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package. - Luke Marris; Ian Gemp; Siqi Liu 002; Joel Z. Leibo; Georgios Piliouras (CoRR, 2024)

Convex Markov Games: A Framework for Fairness, Imitation, and Creativity in Multi-Agent Learning. - Ian Gemp; Andreas Haupt; Luke Marris; Siqi Liu 002; Georgios Piliouras (CoRR, 2024)

Nash Equilibria via Stochastic Eigendecomposition. - Ian Gemp (CoRR, 2024)

Charting the Shapes of Stories with Game Theory. - Constantinos Daskalakis; Ian Gemp; Yanchen Jiang; Renato Paes Leme; Christos H. Papadimitriou; Georgios Piliouras (CoRR, 2024)

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

Re-evaluating Open-ended Evaluation of Large Language Models. - Siqi Liu 002; Ian Gemp; Luke Marris; Georgios Piliouras; Nicolas Heess; Marc Lanctot (ICLR, 2025)

Game of Thoughts: Iterative Reasoning in Game-Theoretic Domains with Large Language Models. - Benjamin Kempinski; Ian Gemp; Kate Larson; Marc Lanctot; Yoram Bachrach; Tal Kachman (AAMAS, 2025)

Soft Condorcet Optimization for Ranking of General Agents. - Marc Lanctot; Kate Larson; Michael Kaisers; Quentin Berthet; Ian Gemp; Manfred Diaz; Roberto-Rafael Maura-Rivero; Yoram Bachrach; Anna Koop; Doina Precup (AAMAS, 2025)

Deviation Ratings: A General, Clone-Invariant Rating Method. - Luke Marris; Siqi Liu 002; Ian Gemp; Georgios Piliouras; Marc Lanctot (CoRR, 2025)

LLM-Mediated Guidance of MARL Systems. - Philipp Dominic Siedler; Ian Gemp (CoRR, 2025)

Solving Zero-Sum Convex Markov Games. - Fivos Kalogiannis; Emmanouil-Vasileios Vlatakis-Gkaragkounis; Ian Gemp; Georgios Piliouras (CoRR, 2025)