Murat Kocaoglu

76 papers A* 25A 8B 1Journal 35Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Decomposing Epistemic Uncertainty for Causal Decision Making. CoRR Md. Musfiqur Rahman, Ziwei Jiang, Hilaf Hasson, Murat Kocaoglu
2025	A	`conf`	Causal Discovery-Driven Change Point Detection in Time Series. AISTATS Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu
2025	J	`jnl`	Characterization and Learning of Causal Graphs from Hard Interventions. CoRR Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
2025	A	`conf`	Constraint-based Causal Discovery from a Collection of Conditioning Sets. UAI Kenneth Lee, Bruno Ribeiro, Murat Kocaoglu
2025	J	`jnl`	Differentiable Constraint-Based Causal Discovery. CoRR Jincheng Zhou, Mengbo Wang, Anqi He, Yumeng Zhou, Hessam Olya, Murat Kocaoglu, Bruno Ribeiro
2025	J	`jnl`	Entropic Causal Inference: Graph Identifiability. CoRR Spencer Compton, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu
2025	A	`conf`	FeDCM: Federated Learning of Deep Causal Generative Models. UAI Md. Musfiqur Rahman, Murat Kocaoglu
2025	J	`jnl`	Identification of Average Outcome under Interventions in Confounded Additive Noise Models. Trans. Mach. Learn. Res. Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
2025	A	`conf`	Root Cause Analysis of Failures from Partial Causal Structures. UAI Azam Ikram, Kenneth Lee, Shubham Agarwal, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu
2024	A*	`conf`	Adaptive Online Experimental Design for Causal Discovery. ICML Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu, Mahsa Ghasemi
2024	J	`jnl`	Adaptive Online Experimental Design for Causal Discovery. CoRR Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu, Mahsa Ghasemi
2024	J	`jnl`	Causal Discovery in Semi-Stationary Time Series. CoRR Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu
2024	J	`jnl`	Causal Discovery-Driven Change Point Detection in Time Series. CoRR Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu
2024	A*	`conf`	Conditional Common Entropy for Instrumental Variable Testing and Partial Identification. ICML Ziwei Jiang, Murat Kocaoglu
2024	A*	`conf`	Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand. NeurIPS Md. Musfiqur Rahman, Matt Jordan, Murat Kocaoglu
2024	J	`jnl`	Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand. CoRR Md. Musfiqur Rahman, Matt Jordan, Murat Kocaoglu
2024	A*	`conf`	Counterfactual Fairness by Combining Factual and Counterfactual Predictions. NeurIPS Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024	J	`jnl`	Counterfactual Fairness by Combining Factual and Counterfactual Predictions. CoRR Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024	A*	`conf`	Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference. ICML Md. Musfiqur Rahman, Murat Kocaoglu
2024	J	`jnl`	Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference. CoRR Md. Musfiqur Rahman, Murat Kocaoglu
2024	A*	`conf`	Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits. NeurIPS Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
2024	J	`jnl`	Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits. CoRR Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
2024	A*	`conf`	Sample Efficient Bayesian Learning of Causal Graphs from Interventions. NeurIPS Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
2024	J	`jnl`	Sample Efficient Bayesian Learning of Causal Graphs from Interventions. CoRR Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
2024	A*	`conf`	Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models. ICLR Zeyu Zhou, Ruqi Bai, Sean Kulinski, Murat Kocaoglu, David I. Inouye
2023	A*	`conf`	Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders. NeurIPS Lai Wei, Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
2023	A*	`conf`	Approximate Causal Effect Identification under Weak Confounding. ICML Ziwei Jiang, Lai Wei, Murat Kocaoglu
2023	J	`jnl`	Approximate Causal Effect Identification under Weak Confounding. CoRR Ziwei Jiang, Lai Wei, Murat Kocaoglu
2023	A*	`conf`	Causal Discovery in Semi-Stationary Time Series. NeurIPS Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu
2023	A*	`conf`	Characterization and Learning of Causal Graphs with Small Conditioning Sets. NeurIPS Murat Kocaoglu
2023	J	`jnl`	Characterization and Learning of Causal Graphs with Small Conditioning Sets. CoRR Murat Kocaoglu
2023	A	`conf`	Finding Invariant Predictors Efficiently via Causal Structure. UAI Kenneth Lee, Md. Musfiqur Rahman, Murat Kocaoglu
2023	A*	`conf`	Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge. NeurIPS Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
2023	J	`jnl`	Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge. CoRR Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
2023	A	`conf`	Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. AISTATS Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
2023	J	`jnl`	Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. CoRR Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
2023	J	`jnl`	Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models. CoRR Sean Kulinski, Zeyu Zhou, Ruqi Bai, Murat Kocaoglu, David I. Inouye
2022	A*	`conf`	Entropic Causal Inference: Graph Identifiability. ICML Spencer Compton, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu
2022	A*	`conf`	Root Cause Analysis of Failures in Microservices through Causal Discovery. NeurIPS Azam Ikram, Sarthak Chakraborty, Subrata Mitra, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu
2021	A	`conf`	Conditionally independent data generation. UAI Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
2021	J	`jnl`	Entropic Causal Inference: Identifiability and Finite Sample Results. CoRR Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
2020	J	`jnl`	Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Active Structure Learning of Causal DAGs via Directed Clique Trees. NeurIPS Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Applications of Common Entropy for Causal Inference. NeurIPS Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath
2020	A*	`conf`	Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning. NeurIPS Amin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim
2020	A*	`conf`	Entropic Causal Inference: Identifiability and Finite Sample Results. NeurIPS Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
2019	A*	`conf`	Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions. NeurIPS Murat Kocaoglu, Amin Jaber, Karthikeyan Shanmugam, Elias Bareinboim
2019	J	`jnl`	Reports of the AAAI 2019 Spring Symposium Series. AI Mag. Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson
2019	A*	`conf`	Sample Efficient Active Learning of Causal Trees. NeurIPS Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler
2018	—	`conf`	CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training. ICLR (Poster) Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis, Sriram Vishwanath
2018	J	`jnl`	Entropic Latent Variable Discovery. CoRR Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath
2018	A*	`conf`	Experimental Design for Cost-Aware Learning of Causal Graphs. NeurIPS Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2018	J	`jnl`	Experimental Design for Cost-Aware Learning of Causal Graphs. CoRR Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2017	J	`jnl`	CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training. CoRR Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis, Sriram Vishwanath
2017	A	`conf`	Contextual Bandits with Latent Confounders: An NMF Approach. AISTATS Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai
2017	A*	`conf`	Cost-Optimal Learning of Causal Graphs. ICML Murat Kocaoglu, Alex Dimakis, Sriram Vishwanath
2017	J	`jnl`	Cost-Optimal Learning of Causal Graphs. CoRR Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2017	J	`jnl`	Energy Minimization With Network Coding via Latin Hypercubes. IEEE Syst. J. Murat Kocaoglu, Özgür B. Akan
2017	A*	`conf`	Entropic Causal Inference. AAAI Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi
2017	J	`jnl`	Entropic Causality and Greedy Minimum Entropy Coupling. CoRR Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi
2017	B	`conf`	Entropie causality anc greedy minimum entropy coupling. ISIT Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi
2017	—	`conf`	Experimental Design for Learning Causal Graphs with Latent Variables. NIPS Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim
2017	J	`jnl`	Sparse Quadratic Logistic Regression in Sub-quadratic Time. CoRR Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi
2016	—	`conf`	Diversity in diffusion-based molecular communication channel with drift. ICC Derya Malak, Hamideh Ramezani, Murat Kocaoglu, Özgür B. Akan
2016	J	`jnl`	Entropic Causal Inference. CoRR Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi
2016	J	`jnl`	Latent Contextual Bandits: A Non-Negative Matrix Factorization Approach. CoRR Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai
2015	—	`conf`	Learning Causal Graphs with Small Interventions. NIPS Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2015	J	`jnl`	Learning Causal Graphs with Small Interventions. CoRR Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2014	J	`jnl`	A Smoothed Analysis for Learning Sparse Polynomials. CoRR Alexandros G. Dimakis, Adam R. Klivans, Murat Kocaoglu, Karthikeyan Shanmugam
2014	—	`conf`	Sparse Polynomial Learning and Graph Sketching. NIPS Murat Kocaoglu, Karthikeyan Shanmugam, Alexandros G. Dimakis, Adam R. Klivans
2013	J	`jnl`	Communication theoretic analysis of the synaptic channel for cortical neurons. Nano Commun. Networks Derya Malak, Murat Kocaoglu, Özgür B. Akan
2013	—	`conf`	Effect of channel conditions on inventory database update in supply chains. BlackSeaCom Murat Kocaoglu, Cuneyt Oksuz, Özgür B. Akan
2013	J	`jnl`	Minimum Energy Channel Codes for Nanoscale Wireless Communications. IEEE Trans. Wirel. Commun. Murat Kocaoglu, Özgür B. Akan
2012	J	`jnl`	Fundamentals of Green Communications and Computing: Modeling and Simulation. Computer Murat Kocaoglu, Derya Malak, Özgür B. Akan
2012	A*	`conf`	Minimum energy coding for wireless nanosensor networks. INFOCOM Murat Kocaoglu, Özgür B. Akan
2012	—	`conf`	On the node density limits and rate-delay-energy tradeoffs in ad hoc nanonetworks with minimum energy coding. ICC Murat Kocaoglu, Derya Malak