Alex Boyd

25 papers A* 4A 3Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Not Another Boot Camp: Toward an Inclusive Computational Pedagogy.
Libr. Trends
Dolsy Smith, Daphna Atias, Emily Blumenthal, Alex Boyd, Madeline Doering, Katelyn Morgan, Marcus Peerman, Robin Pokorski, Max Turer
2025 J jnl
Bayesian Inference for Correlated Human Experts and Classifiers.
CoRR
Markelle Kelly, Alex Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth
2025 J jnl
Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point Processes.
CoRR
Alex Boyd, Andrew Warrington, Taha A. Kass-Hout, Parminder Bhatia, Danica Xiao
2025 J jnl
On the Effect of Regularization on Nonparametric Mean-Variance Regression.
CoRR
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2025 J jnl
ST-PPO: Stabilized Off-Policy Proximal Policy Optimization for Multi-Turn Agents Training.
CoRR
Chenliang Li, Adel Elmahdy, Alex Boyd, Zhongruo Wang, Alfredo García, Parminder Bhatia, Taha A. Kass-Hout, Cao Xiao, Mingyi Hong
2024 J jnl
Deep Linear Hawkes Processes.
CoRR
Yuxin Chang, Alex Boyd, Cao Xiao, Taha A. Kass-Hout, Parminder Bhatia, Padhraic Smyth, Andrew Warrington
2024 J jnl
On the Efficient Marginalization of Probabilistic Sequence Models.
CoRR
Alex Boyd
2024 A conf
Understanding Pathologies of Deep Heteroskedastic Regression.
UAI
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2024 J jnl
salmon: A Symbolic Linear Regression Package for
J. Stat. Softw.
Alex Boyd, Dennis L. Sun
2023 J jnl
Bayesian Online Learning for Consensus Prediction.
CoRR
Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers
2023 A conf
Inference for mark-censored temporal point processes.
UAI
Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023 J jnl
Probabilistic Modeling for Sequences of Sets in Continuous-Time.
CoRR
Yuxin Chang, Alex Boyd, Padhraic Smyth
2023 A conf
Probabilistic Querying of Continuous-Time Event Sequences.
AISTATS
Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023 J jnl
Understanding Pathologies of Deep Heteroskedastic Regression.
CoRR
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2022 A* conf
Predictive Querying for Autoregressive Neural Sequence Models.
NeurIPS
Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022 J jnl
Predictive Querying for Autoregressive Neural Sequence Models.
CoRR
Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022 J jnl
Probabilistic Querying of Continuous-Time Event Sequences.
CoRR
Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2021 A* conf
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning.
NeurIPS
Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt
2021 — conf
Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions.
MLHC
Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth
2021 J jnl
Structured Stochastic Gradient MCMC.
CoRR
Antonios Alexos, Alex Boyd, Stephan Mandt
2020 A* conf
Large Scale Multi-Actor Generative Dialog Modeling.
ACL
Alex Boyd, Raul Puri, Mohammad Shoeybi, Mostofa Patwary, Bryan Catanzaro
2020 J jnl
Large Scale Multi-Actor Generative Dialog Modeling.
CoRR
Alex Boyd, Raul Puri, Mohammad Shoeybi, Mostofa Patwary, Bryan Catanzaro
2020 A* conf
User-Dependent Neural Sequence Models for Continuous-Time Event Data.
NeurIPS
Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020 J jnl
User-Dependent Neural Sequence Models for Continuous-Time Event Data.
CoRR
Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020 J jnl
Variational Beam Search for Online Learning with Distribution Shifts.
CoRR
Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt