Sina Akbari

According to our database, Sina Akbari authored at least 18 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers and Fully-Connected Neural Networks for Causally Constrained Predictions.

Matthew J. Vowels, Mathieu Rochat, Sina Akbari

CoRR, 2024

Fast Proxy Experiment Design for Causal Effect Identification.

Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran

CoRR, 2024

Recursive Causal Discovery.

Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari, Negar Kiyavash

CoRR, 2024

Triple Changes Estimator for Targeted Policies.

Sina Akbari, Negar Kiyavash

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Approximate Condorcet Partitioning: Solving large-scale rank aggregation problems.

Sina Akbari, Adolfo R. Escobedo

Comput. Oper. Res., May, 2023

A Free Lunch with Influence Functions? An Empirical Evaluation of Influence Functions for Average Treatment Effect Estimation.

Matthew James Vowels, Sina Akbari, Necati Cihan Camgöz, Richard Bowden

Trans. Mach. Learn. Res., 2023

Learning Causal Graphs via Monotone Triangular Transport Maps.

Sina Akbari, Luca Ganassali, Negar Kiyavash

CoRR, 2023

Causal Imitability Under Context-Specific Independence Relations.

Fateme Jamshidi, Sina Akbari, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Effect Identification in Uncertain Causal Networks.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

CoRR, 2022

A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics.

Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden

CoRR, 2022

Top-k List Aggregation: Mathematical Formulations and Polyhedral Comparisons.

Sina Akbari, Adolfo R. Escobedo

Proceedings of the Combinatorial Optimization - 7th International Symposium, 2022

Minimum Cost Intervention Design for Causal Effect Identification.

Sina Akbari, Jalal Etesami, Negar Kiyavash

Proceedings of the International Conference on Machine Learning, 2022

Learning Bayesian Networks in the Presence of Structural Side Information.

Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Lower Bounds on Kemeny Rank Aggregation with Non-Strict Rankings.

Sina Akbari, Adolfo R. Escobedo

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias.

Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Recursive Markov Boundary-Based Approach to Causal Structure Learning.

Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash

Proceedings of the KDD 2021 Workshop on Causal Discovery, 2021

2020

A Recursive Markov Blanket-Based Approach to Causal Structure Learning.

Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash

CoRR, 2020