Learning with Explanation Constraints
Dylan Sam*, Rattana Pukdee*, J. Zico Kolter, Maria-Florina Balcan, and Pradeep Ravikumar
Neural Information Processing Systems (NeurIPS), 2023

Bayesian Neural Networks with Domain Knowledge
Dylan Sam*, Rattana Pukdee*, Daniel P. Jeong, Yewon Byun, and J. Zico Kolter
ICML Knowledge and Logical Reasoning Workshop (Oral), 2023

Label Propagation with Weak Supervision
Dylan Sam*, Rattana Pukdee*, Maria-Florina Balcan, and Pradeep Ravikumar
International Conference on Learning Representations (ICLR), 2023
[pdf, code]

Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam and J. Zico Kolter
AAAI Conference on Artificial Intelligence, 2023
[pdf, code]


Improving self-supervised representation learning via sequential adversarial masking
Dylan Sam, Min Bai, Tristan McKinney, and Li Erran Li
NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice, 2022


Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto*, Cyrus Cousins*, Dylan Sam, Stephen H Bach, and Eli Upfal
International Conference on Machine Learning (ICML), 2021
[pdf, code]

Semi-Supervised Aggregation of Dependent Weak Supervision Sources with Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, and Stephen H Bach
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
[pdf, code]

Learning from Dependent Weak Supervision Sources
Dylan Sam
Undergraduate Honors Thesis, 2021

Automated Data Accountability for the Mars Science Laboratory
Ryan Alimo, Dylan Sam, Dounia Lakhmiri, Brian Kahovec, and Dariush Divsalar
IEEE Aerospace Conference, 2021
[pdf, code]


Hierarchical Clustering Analysis of Spectral Fingerprints for Cheminformatics
Dylan Sam and Brenda M Rubenstein
NeurIPS Machine Learning for Molecules Workshop, 2020