Alex Boyd

According to our database, Alex Boyd authored at least 21 papers between 2020 and 2026.

Collaborative distances:

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

2026

Not Another Boot Camp: Toward an Inclusive Computational Pedagogy.

Dolsy Smith, Daphna Atias, Emily Blumenthal, Alex Boyd, Madeline Doering, Katelyn Morgan, Marcus Peerman, Robin Pokorski, Max Turer

Libr. Trends, 2026

2025

On the Effect of Regularization on Nonparametric Mean-Variance Regression.

Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt

CoRR, November, 2025

ST-PPO: Stabilized Off-Policy Proximal Policy Optimization for Multi-Turn Agents Training.

Chenliang Li, Adel Elmahdy, Alex Boyd, Zhongruo Wang, Alfredo García, Parminder Bhatia, Taha A. Kass-Hout, Cao Xiao, Mingyi Hong

CoRR, November, 2025

Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point Processes.

Alex Boyd, Andrew Warrington, Taha A. Kass-Hout, Parminder Bhatia, Danica Xiao

CoRR, November, 2025

Bayesian Inference for Correlated Human Experts and Classifiers.

Markelle Kelly, Alex James Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning.

Aofei Chang, Le Huang, Alex James Boyd, Parminder Bhatia, Taha A. Kass-Hout, Cao Xiao, Fenglong Ma

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

salmon: A Symbolic Linear Regression Package for <i>Python</i>.

Alex Boyd, Dennis L. Sun

J. Stat. Softw., 2024

Deep Linear Hawkes Processes.

Yuxin Chang, Alex Boyd, Cao Xiao, Taha A. Kass-Hout, Parminder Bhatia, Padhraic Smyth, Andrew Warrington

CoRR, 2024

On the Efficient Marginalization of Probabilistic Sequence Models.

Alex Boyd

CoRR, 2024

Understanding Pathologies of Deep Heteroskedastic Regression.

Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Bayesian Online Learning for Consensus Prediction.

Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Probabilistic Modeling for Sequences of Sets in Continuous-Time.

Yuxin Chang, Alex J. Boyd, Padhraic Smyth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Inference for mark-censored temporal point processes.

Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Probabilistic Querying of Continuous-Time Event Sequences.

Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Predictive Querying for Autoregressive Neural Sequence Models.

Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Structured Stochastic Gradient MCMC.

Antonios Alexos, Alex J. Boyd, Stephan Mandt

Proceedings of the International Conference on Machine Learning, 2022

2021

Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning.

Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt

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

Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions.

Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Variational Beam Search for Online Learning with Distribution Shifts.

Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt

CoRR, 2020

User-Dependent Neural Sequence Models for Continuous-Time Event Data.

Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Large Scale Multi-Actor Generative Dialog Modeling.

Alex Boyd, Raul Puri, Mohammad Shoeybi, Mostofa Patwary, Bryan Catanzaro

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020