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Robert E. Tillman
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2020 – today
- 2024
- [i5]Zixiang Chen, Jun Han, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu:
Guided Discrete Diffusion for Electronic Health Record Generation. CoRR abs/2404.12314 (2024) - 2023
- [j1]Robert E. Tillman, Tucker Balch, Manuela Veloso:
Privacy-Preserving Energy-Based Generative Models for Marginal Distribution Protection. Trans. Mach. Learn. Res. 2023 (2023) - [i4]Penghang Liu, Rupam Acharyya, Robert E. Tillman, Shunya Kimura, Naoki Masuda
, Ahmet Erdem Sariyüce:
Temporal Motifs for Financial Networks: A Study on Mercari, JPMC, and Venmo Platforms. CoRR abs/2301.07791 (2023) - 2022
- [i3]Parisa Hassanzadeh, Robert E. Tillman:
Generative Models with Information-Theoretic Protection Against Membership Inference Attacks. CoRR abs/2206.00071 (2022) - 2020
- [c8]Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant P. Reddy, Manuela Veloso:
Heuristics for Link Prediction in Multiplex Networks. ECAI 2020: 1938-1945 - [c7]Robert E. Tillman, Prashant P. Reddy, Manuela Veloso:
Recommending missing and suspicious links in multiplex financial networks. ICAIF 2020: 20:1-20:8 - [c6]Samuel A. Assefa, Danial Dervovic, Mahmoud Mahfouz, Robert E. Tillman, Prashant Reddy, Manuela Veloso:
Generating synthetic data in finance: opportunities, challenges and pitfalls. ICAIF 2020: 44:1-44:8 - [i2]Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant P. Reddy, Manuela M. Veloso:
Heuristics for Link Prediction in Multiplex Networks. CoRR abs/2004.04704 (2020) - [i1]Chirag Nagpal, Robert E. Tillman, Prashant P. Reddy, Manuela Veloso:
Latent Bayesian Inference for Robust Earnings Estimates. CoRR abs/2004.06565 (2020)
2010 – 2019
- 2011
- [c5]Robert E. Tillman, Peter Spirtes:
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables. AISTATS 2011: 3-15 - 2010
- [c4]Robert E. Tillman, Peter Spirtes:
When causality matters for prediction. NIPS Causality: Objectives and Assessment 2010: 137-146
2000 – 2009
- 2009
- [c3]Robert E. Tillman:
Structure learning with independent non-identically distributed data. ICML 2009: 1041-1048 - [c2]Robert E. Tillman, Arthur Gretton, Peter Spirtes:
Nonlinear directed acyclic structure learning with weakly additive noise models. NIPS 2009: 1847-1855 - 2008
- [c1]Robert E. Tillman, David Danks, Clark Glymour:
Integrating Locally Learned Causal Structures with Overlapping Variables. NIPS 2008: 1665-1672
Coauthor Index
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