| 2026 | AAAI | Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. | Larkin Liu, Kashif Rasul, Yutong Chao, Jalal Etesami |
| 2025 | ICML | Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization. | Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser |
| 2023 | AAAI | Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. | Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash |
| 2023 | UAI | On Identifiability of Conditional Causal Effects. | Yaroslav Kivva, Jalal Etesami, Negar Kiyavash |
| 2022 | AAAI | Learning Bayesian Networks in the Presence of Structural Side Information. | Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash |
| 2022 | AISTATS | Causal Effect Identification with Context-specific Independence Relations of Control Variables. | Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash |
| 2022 | ICML | Minimum Cost Intervention Design for Causal Effect Identification. | Sina Akbari, Jalal Etesami, Negar Kiyavash |
| 2022 | UAI | Revisiting the general identifiability problem. | Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash |
| 2021 | AISTATS | A Variational Inference Approach to Learning Multivariate Wold Processes. | Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran |
| 2021 | ICML | Cumulants of Hawkes Processes are Robust to Observation Noise. | William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran |
| 2020 | AAAI | Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift. | Jalal Etesami, Philipp Geiger |
| 2019 | ICML | Learning Hawkes Processes Under Synchronization Noise. | William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran |
| 2018 | AAAI | Learning Vector Autoregressive Models With Latent Processes. | Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang |
| 2017 | ACSSC | Efficient neighborhood selection for walk summable Gaussian graphical models. | Yingxang Yang, Jalal Etesami, Negar Kiyavash |
| 2017 | ISIT | Identifying nonlinear 1-step causal influences in presence of latent variables. | Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash |
| 2016 | ISIT | Interventional dependency graphs: An approach for discovering influence structure. | Jalal Etesami, Negar Kiyavash |
| 2016 | UAI | Learning Network of Multivariate Hawkes Processes: A Time Series Approach. | Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal |
| 2014 | ISIT | A novel collusion attack on finite alphabet digital fingerprinting systems. | Jalal Etesami, Negar Kiyavash |
| 2013 | ISIT | Robust directed tree approximations for networks of stochastic processes. | Christopher J. Quinn, Jalal Etesami, Negar Kiyavash, Todd P. Coleman |
| 2012 | ISIT | Learning minimal latent directed information trees. | Jalal Etesami, Negar Kiyavash, Todd P. Coleman |
| 2011 | GLOBECOM | LCD Codes and Iterative Decoding by Projections, a First Step Towards an Intuitive Description of Iterative Decoding. | Jalal Etesami, Fangning Hu, Werner Henkel |