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2020 – today
- 2025
[c13]Aofei Chang, Le Huang, Alex James Boyd, Parminder Bhatia, Taha A. Kass-Hout, Cao Xiao, Fenglong Ma:
Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning. ACL (1) 2025: 9357-9372- [c12]Markelle Kelly, Alex James Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth:
Bayesian Inference for Correlated Human Experts and Classifiers. ICML 2025 - [i14]Aofei Chang, Le Huang, Alex J. Boyd, Parminder Bhatia, Taha A. Kass-Hout, Cao Xiao, Fenglong Ma:
Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning. CoRR abs/2505.18503 (2025) - [i13]Markelle Kelly, Alex Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth:
Bayesian Inference for Correlated Human Experts and Classifiers. CoRR abs/2506.05636 (2025) - [i12]Alex Boyd, Andrew Warrington, Taha A. Kass-Hout, Parminder Bhatia, Danica Xiao:
Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point Processes. CoRR abs/2511.01096 (2025) - 2024
- [j1]Alex Boyd, Dennis L. Sun:
salmon: A Symbolic Linear Regression Package for Python. J. Stat. Softw. 108(8) (2024) - [c11]Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers:
Bayesian Online Learning for Consensus Prediction. AISTATS 2024: 2539-2547 - [c10]Yuxin Chang, Alex J. Boyd, Padhraic Smyth:
Probabilistic Modeling for Sequences of Sets in Continuous-Time. AISTATS 2024: 4357-4365 - [c9]Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt:
Understanding Pathologies of Deep Heteroskedastic Regression. UAI 2024: 3765-3790 - [i11]Alex Boyd:
On the Efficient Marginalization of Probabilistic Sequence Models. CoRR abs/2403.04005 (2024) - [i10]Yuxin Chang, Alex Boyd, Cao Xiao, Taha A. Kass-Hout, Parminder Bhatia, Padhraic Smyth, Andrew Warrington:
Deep Linear Hawkes Processes. CoRR abs/2412.19634 (2024) - 2023
- [c8]Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Probabilistic Querying of Continuous-Time Event Sequences. AISTATS 2023: 10235-10251 - [c7]Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Inference for mark-censored temporal point processes. UAI 2023: 226-236 - [i9]Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt:
Understanding Pathologies of Deep Heteroskedastic Regression. CoRR abs/2306.16717 (2023) - [i8]Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers:
Bayesian Online Learning for Consensus Prediction. CoRR abs/2312.07679 (2023) - [i7]Yuxin Chang, Alex Boyd, Padhraic Smyth:
Probabilistic Modeling for Sequences of Sets in Continuous-Time. CoRR abs/2312.15045 (2023) - 2022
- [c6]Antonios Alexos, Alex J. Boyd, Stephan Mandt:
Structured Stochastic Gradient MCMC. ICML 2022: 414-434 - [c5]Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth:
Predictive Querying for Autoregressive Neural Sequence Models. NeurIPS 2022 - [i6]Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth:
Predictive Querying for Autoregressive Neural Sequence Models. CoRR abs/2210.06464 (2022) - [i5]Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Probabilistic Querying of Continuous-Time Event Sequences. CoRR abs/2211.08499 (2022) - 2021
- [c4]Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth:
Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions. MLHC 2021: 648-673 - [c3]Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt:
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. NeurIPS 2021: 6816-6828 - [i4]Antonios Alexos, Alex Boyd, Stephan Mandt:
Structured Stochastic Gradient MCMC. CoRR abs/2107.09028 (2021) - 2020
- [c2]Alex Boyd, Raul Puri, Mohammad Shoeybi, Mostofa Patwary, Bryan Catanzaro:
Large Scale Multi-Actor Generative Dialog Modeling. ACL 2020: 66-84 - [c1]Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth:
User-Dependent Neural Sequence Models for Continuous-Time Event Data. NeurIPS 2020 - [i3]Alex Boyd, Raul Puri, Mohammad Shoeybi, Mostofa Patwary, Bryan Catanzaro:
Large Scale Multi-Actor Generative Dialog Modeling. CoRR abs/2005.06114 (2020) - [i2]Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth:
User-Dependent Neural Sequence Models for Continuous-Time Event Data. CoRR abs/2011.03231 (2020) - [i1]Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt:
Variational Beam Search for Online Learning with Distribution Shifts. CoRR abs/2012.08101 (2020)
Coauthor Index
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