Theodore Papamarkou
7 papers · 2018–2024 · 4 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 👥 Mega-Team · Squad
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The Questioner
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Prolific Year · Productive
Venues
Top co-authors
Research topics
Keywords
posterior sampling
(2)
bayesian inference
(2)
markov chain monte carlo
(2)
bayesian neural network
(2)
neural network
(2)
interpretability
(1)
geometric deep learning
(1)
graph representation
(1)
gaussian process
(1)
message passing
(1)
graph embedding
(1)
parameter inference
(1)
model averaging
(1)
foundation model
(1)
bayesian deep learning
(1)
ordinary differential equation
(1)
topological feature
(1)
infinite width
(1)
deep ensemble
(1)
simplicial complex
(1)
Papers
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
ICML 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
ICML 2024
Position: Topological Deep Learning is the New Frontier for Relational Learning
ICML 2024
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains
JMLR 2024
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract)
IJCAI 2024
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes
JMLR 2020
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations
AISTATS 2018