Arjun Ravi Kannan

15 papers Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MS-IMAP - A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning. Trans. Mach. Learn. Res. Shay Deutsch, Lionel Yelibi, Alex Tong Lin, Arjun Ravi Kannan
2025	J	`jnl`	Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews. CoRR Izunna Okpala, Ashkan Golgoon, Arjun Ravi Kannan
2025	—	`conf`	Human-Centered Agentic Framework for Machine Learning Modeling in Finance. SOSE Izunna Okpala, Ashkan Golgoon, Arjun Ravi Kannan
2025	J	`jnl`	MbExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings. Mach. Learn. Ashkan Golgoon, Ryan Franks, Khashayar Filom, Arjun Ravi Kannan
2024	J	`jnl`	MBExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings. CoRR Ashkan Golgoon, Ryan Franks, Khashayar Filom, Arjun Ravi Kannan
2024	J	`jnl`	MS-IMAP - A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning. CoRR Shay Deutsch, Lionel Yelibi, Alex Tong Lin, Arjun Ravi Kannan
2024	—	`conf`	Mechanistic interpretability of large language models with applications to the financial services industry. ICAIF Ashkan Golgoon, Khashayar Filom, Arjun Ravi Kannan
2024	J	`jnl`	Mechanistic interpretability of large language models with applications to the financial services industry. CoRR Ashkan Golgoon, Khashayar Filom, Arjun Ravi Kannan
2023	J	`jnl`	Approximation of group explainers with coalition structure using Monte Carlo sampling on the product space of coalitions and features. CoRR Konstandinos Kotsiopoulos, Alexey Miroshnikov, Khashayar Filom, Arjun Ravi Kannan
2023	J	`jnl`	On marginal feature attributions of tree-based models. CoRR Khashayar Filom, Alexey Miroshnikov, Konstandinos Kotsiopoulos, Arjun Ravi Kannan
2022	J	`jnl`	Wasserstein-based fairness interpretability framework for machine learning models. Mach. Learn. Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan
2021	J	`jnl`	A United States Fair Lending Perspective on Machine Learning. Frontiers Artif. Intell. Patrick Hall, Benjamin Cox, Steven Dickerson, Arjun Ravi Kannan, Raghu Kulkarni, Nicholas Schmidt
2021	J	`jnl`	Model-agnostic bias mitigation methods with regressor distribution control for Wasserstein-based fairness metrics. CoRR Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan
2021	J	`jnl`	Mutual information-based group explainers with coalition structure for machine learning model explanations. CoRR Alexey Miroshnikov, Konstandinos Kotsiopoulos, Arjun Ravi Kannan
2020	J	`jnl`	Wasserstein-based fairness interpretability framework for machine learning models. CoRR Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan