Key papers

• TerraNova: A Foundation Model for the Anthropocene (2026)
  Carlos Rodriguez-Pardo et al.
  3.45
• Distance Profile Embedding for Independence and Conditional Independence Testing of Random Objects (2026)
  Wenxi Tan et al.
  1.94
• Identification and Inference in Nonlinear Dynamic Network Models (2026)
  Diego Vallarino
  1.78
• Causal inference for social network formation (2026)
  Maximilian Kasy and Elizabeth Linos and Sanaz Mobasseri
  1.78
• Fast Response or Silence: Conversation Persistence in an AI-Agent Social Network (2026)
  Aysajan Eziz
  1.67
• On Evolution-Based Models for Experimentation Under Interference (2025)
  Sadegh Shirani and Mohsen Bayati
  1.50
• Stock Market Telepathy: Graph Neural Networks Predicting the Secret Conversations between MINT and G7 Countries (2025)
  Nurbanu Bursa
  1.22
• Doubly robust estimation of causal effects for random object outcomes with continuous treatments (2025)
  Satarupa Bhattacharjee et al.
  1.22
• Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks (2025)
  Francesco Cozzi et al.
  1.17
• Designing Graph Convolutional Neural Networks for Discrete Choice with Network Effects (2025)
  Daniel F. Villarraga and Ricardo A. Daziano
  1.06
• Estimating Network Models using Neural Networks (2025)
  Angelo Mele
  1.00
• Sparse network asymptotics for logistic regression (2020)
  Bryan S. Graham
  —
• Causal motifs and existence of endogenous cascades in directed networks with application to company defaults (2020)
  Irena Barja\v{s}i\'c et al.
  —
• Tree-based Node Aggregation in Sparse Graphical Models (2021)
  Ines Wilms and Jacob Bien
  —
• The Local Approach to Causal Inference under Network Interference (2021)
  Eric Auerbach and Hongchang Guo and Max Tabord-Meehan
  —
• Asymptotic in a class of network models with an increasing sub-Gamma degree sequence (2021)
  Jing Luo et al.
  —
• Network regression and supervised centrality estimation (2021)
  Junhui Cai et al.
  —
• Learning with latent group sparsity via heat flow dynamics on networks (2022)
  Subhroshekhar Ghosh and Soumendu Sundar Mukherjee
  —
• Graph-Based Methods for Discrete Choice (2022)
  Kiran Tomlinson and Austin R. Benson
  —
• A new mapping of technological interdependence (2023)
  A. Fronzetti Colladon et al.
  —
• Predicting Financial Literacy via Semi-supervised Learning (2023)
  David Hason Rudd et al.
  —
• Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework (2023)
  Jalal Etesami and Ali Habibnia and Negar Kiyavash
  —
• Deep Learning With DAGs (2024)
  Sourabh Balgi et al.
  —
• Non-robustness of diffusion estimates on networks with measurement error (2024)
  Arun G. Chandrasekhar and Paul Goldsmith-Pinkham and Tyler H. McCormick and Samuel Thau and Jerry Wei
  —
• Estimating Dyadic Treatment Effects with Unknown Confounders (2024)
  Tadao Hoshino et al.
  —
• Model-Based Inference and Experimental Design for Interference Using Partial Network Data (2024)
  Steven Wilkins Reeves et al.
  —
• Collusion Detection with Graph Neural Networks (2024)
  Lucas Gomes et al.
  —