Recency, records and recaps: learning and non-equilibrium behavior in a simple decision problem. - Drew Fudenberg; Alexander Peysakhovich (EC, 2014)

The Good, the Bad, and the Unflinchingly Selfish: Cooperative Decision-Making can be Predicted with high Accuracy when using only Three Behavioral Types. - Ziv Epstein; Alexander Peysakhovich; David G. Rand (EC, 2016)

Combining observational and experimental data to find heterogeneous treatment effects. - Alexander Peysakhovich; Akos Lada (CoRR, 2016)

Asymmetric Effects of Favorable and Unfavorable Information on Decision Making Under Ambiguity. - Alexander Peysakhovich; Uma R. Karmarkar (Manag. Sci., 2016)

Habits of Virtue: Creating Norms of Cooperation and Defection in the Laboratory. - Alexander Peysakhovich; David G. Rand (Manag. Sci., 2016)

Recency, Records, and Recaps: Learning and Nonequilibrium Behavior in a Simple Decision Problem. - Drew Fudenberg; Alexander Peysakhovich (ACM Trans. Economics and Comput., 2016)

Multi-Agent Cooperation and the Emergence of (Natural) Language. - Angeliki Lazaridou; Alexander Peysakhovich; Marco Baroni (ICLR, 2017)

Learning context-dependent preferences from raw data. - Alexander Peysakhovich; Johan Ugander (NetEcon@EC, 2017)

Maintaining cooperation in complex social dilemmas using deep reinforcement learning. - Adam Lerer; Alexander Peysakhovich (CoRR, 2017)

Consequentialist Conditional Cooperation in Social Dilemmas with Imperfect Information (Short Workshop Version). - Alexander Peysakhovich; Adam Lerer (AAAI Workshops, 2018)

Towards AI that Can Solve Social Dilemmas. - Alexander Peysakhovich; Adam Lerer (AAAI Spring Symposia, 2018)

Prosocial Learning Agents Solve Generalized Stag Hunts Better than Selfish Ones. - Alexander Peysakhovich; Adam Lerer (AAMAS, 2018)

Consequentialist conditional cooperation in social dilemmas with imperfect information. - Alexander Peysakhovich; Adam Lerer (ICLR (Poster), 2018)

Learning Causal Effects From Many Randomized Experiments Using Regularized Instrumental Variables. - Alexander Peysakhovich; Dean Eckles (WWW, 2018)

Learning Social Conventions in Markov Games. - Adam Lerer; Alexander Peysakhovich (CoRR, 2018)

Backplay: "Man muss immer umkehren". - Cinjon Resnick; Roberta Raileanu; Sanyam Kapoor; Alex Peysakhovich; Kyunghyun Cho; Joan Bruna (CoRR, 2018)

Improving pairwise comparison models using Empirical Bayes shrinkage. - Stephen Ragain; Alexander Peysakhovich; Johan Ugander (CoRR, 2018)

Learning Existing Social Conventions via Observationally Augmented Self-Play. - Adam Lerer; Alexander Peysakhovich (AIES, 2019)

Reinforcement Learning and Inverse Reinforcement Learning with System 1 and System 2. - Alexander Peysakhovich (AIES, 2019)

Observational Data for Heterogeneous Treatment Effects with Application to Recommender Systems. - Akos Lada; Alexander Peysakhovich; Diego Aparicio; Michael Bailey (EC, 2019)

Discovering Context Effects from Raw Choice Data. - Arjun Seshadri; Alex Peysakhovich; Johan Ugander (ICML, 2019)

Pytorch-BigGraph: A Large Scale Graph Embedding System. - Adam Lerer; Ledell Wu; Jiajun Shen; Timothée Lacroix; Luca Wehrstedt; Abhijit Bose; Alex Peysakhovich (SysML, 2019)

Robust Multi-agent Counterfactual Prediction. - Alexander Peysakhovich; Christian Kroer; Adam Lerer (NeurIPS, 2019)

Fair Division Without Disparate Impact. - Alexander Peysakhovich; Christian Kroer (CoRR, 2019)

Scalable Fair Division for 'At Most One' Preferences. - Christian Kroer; Alexander Peysakhovich (CoRR, 2019)

The Good, the Bad, and the Unflinchingly Selfish: Pro-sociality can be Well Predicted Using Payoffs and Three Behavioral Types. - Ziv Epstein; Alexander Peysakhovich; David G. Rand (ACM Trans. Economics and Comput., 2019)

Robust Market Equilibria with Uncertain Preferences. - Riley Murray; Christian Kroer; Alex Peysakhovich; Parikshit Shah (AAAI, 2020)

"Other-Play" for Zero-Shot Coordination. - Hengyuan Hu; Adam Lerer; Alex Peysakhovich; Jakob N. Foerster (ICML, 2020)

Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. - Jack Parker-Holder; Luke Metz; Cinjon Resnick; Hengyuan Hu; Adam Lerer; Alistair Letcher; Alexander Peysakhovich; Aldo Pacchiano; Jakob N. Foerster (NeurIPS, 2020)

Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions. - Tom Yan; Christian Kroer; Alexander Peysakhovich (NeurIPS, 2020)

Online Market Equilibrium with Application to Fair Division. - Yuan Gao; Alex Peysakhovich; Christian Kroer (NeurIPS, 2021)

An Attract-Repel Decomposition of Undirected Networks. - Alexander Peysakhovich; Léon Bottou (CoRR, 2021)

Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes. - Leon Yao; Caroline Lo; Israel Nir; Sarah Tan; Ariel Evnine; Adam Lerer; Alex Peysakhovich (CoRR, 2022)

Parity in Markets - Methods, Costs, and Consequences. - Alexander Peysakhovich; Christian Kroer; Nicolas Usunier (CoRR, 2022)

Computing Large Market Equilibria Using Abstractions. - Christian Kroer; Alexander Peysakhovich; Eric Sodomka; Nicolás E. Stier Moses (Oper. Res., 2022)

Implementing Fairness Constraints in Markets Using Taxes and Subsidies. - Alexander Peysakhovich; Christian Kroer; Nicolas Usunier (FAccT, 2023)

Diagnosis Uncertain Models For Medical Risk Prediction. - Alexander Peysakhovich; Rich Caruana; Yin Aphinyanaphongs (CoRR, 2023)

Attention Sorting Combats Recency Bias In Long Context Language Models. - Alexander Peysakhovich; Adam Lerer (CoRR, 2023)

MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data. - William Berman; Alexander Peysakhovich (CoRR, 2024)