Mike Gartrell
9 papers · 2019–2026 · 6 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Silver
🏃
Academic Marathon · Sprint
🌉
Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(25)
🐣
Hot Topic Early Bird
Top co-authors
Research topics
Machine Learning
(8)
Bayesian & Probabilistic · Machine Learning
(5)
Optimization & Theory
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Mathematics & Optimization
(3)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Learning Types
(3)
Core Methods
(2)
Models
(2)
Optimization
(2)
Data Science & Analytics
(1)
Natural Language Processing
(1)
Application Areas
(1)
Applications
(1)
Keywords
determinantal point process
(4)
kernel matrix
(3)
gradient flow
(2)
maximum likelihood estimation
(2)
rejection sampling
(2)
subset selection
(2)
optimal transport
(2)
text generation
(1)
maximum mean discrepancy
(1)
domain adaptation
(1)
markov chain monte carlo
(1)
scalable learning
(1)
prompt learning
(1)
probability measure
(1)
maximum a posteriori inference
(1)
information retrieval
(1)
generative model
(1)
disentangled representation
(1)
variational autoencoder
(1)
bayesian inference
(1)
Papers
ReBaPL: Repulsive Bayesian Prompt Learning
CVPR 2026
Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation
UAI 2026
Learning from Multiple Sources for Data-to-Text and Text-to-Data
AISTATS 2023
Unifying GANs and Score-Based Diffusion as Generative Particle Models
NeurIPS 2023
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
ICML 2022
Scalable Sampling for Nonsymmetric Determinantal Point Processes
ICLR 2022
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
ICLR 2021
Learning Determinantal Point Processes by Corrective Negative Sampling
AISTATS 2019
Learning Nonsymmetric Determinantal Point Processes
NeurIPS 2019