Katie E Everett
5 papers · 2022–2024 · 3 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Bronze
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Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(15)
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Conference Pioneer
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Research topics
Machine Learning
(5)
Deep Learning
(3)
Artificial Intelligence
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Core AI
(2)
Models
(2)
Optimization & Theory
(2)
Mathematics & Optimization
(1)
Architectures
(1)
Bayesian & Probabilistic · Artificial Intelligence
(1)
Core Methods
(1)
Learning Types
(1)
Optimization
(1)
Techniques
(1)
Keywords
variational autoencoder
(2)
variational inference
(2)
expectation maximization
(1)
neural network optimization
(1)
importance sampling
(1)
learning rate
(1)
latent variable model
(1)
multimodal distribution
(1)
disentangled representation
(1)
gradient norm
(1)
generative flow network
(1)
latent factor
(1)
off-policy training
(1)
causal graphical model
(1)
training instability
(1)
discrete structure
(1)
gradient underflow
(1)
learning rate scaling
(1)
discrete variational autoencoder
(1)
mechanism sparsity
(1)
Papers
Scaling Exponents Across Parameterizations and Optimizers
ICML 2024
Small-scale proxies for large-scale Transformer training instabilities
ICLR 2024
GFlowNet-EM for Learning Compositional Latent Variable Models
ICML 2023
GFlowNets and variational inference
ICLR 2023
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
CLeaR 2022