Mike Wu
9 papers · 2018–2022 · 4 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer π Conference Polyglot (4) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (33)
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Cross-Pollinator
(8)
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Renaissance Researcher
(5)
π₯
Unstoppable
(5)
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Conference Pioneer
Conferences
AAAI (3)
NIPS (3)
ICLR (2)
AISTATS (1)
Top co-authors
Research topics
Keywords
generative model
(3)
neural network
(2)
variational inference
(2)
amortized inference
(2)
variational autoencoder
(2)
multi-modal learning
(1)
weakly supervised learning
(1)
zero-shot learning
(1)
posterior inference
(1)
monte carlo estimation
(1)
weakly-supervised learning
(1)
variance reduction
(1)
monte carlo sampling
(1)
probabilistic programming
(1)
transfer learning
(1)
latent representation
(1)
neural network interpretability
(1)
stochastic variational inference
(1)
deep neural network
(1)
image translation
(1)
Papers
Foundation Posteriors for Approximate Probabilistic Inference
NIPS 2022
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
ICLR 2021
Improving Compositionality of Neural Networks by Decoding Representations to Inputs
NIPS 2021
Conditional Negative Sampling for Contrastive Learning of Visual Representations
ICLR 2021
Meta-Amortized Variational Inference and Learning
AAAI 2020
Regional Tree Regularization for Interpretability in Deep Neural Networks
AAAI 2020
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference
AISTATS 2019
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
AAAI 2019
Multimodal Generative Models for Scalable Weakly-Supervised Learning
NIPS 2018