Jonathan Gordon
11 papers · 2016–2021 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (27) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird
🏆
Grand Slam
👑
Triple Crown
⚡
Prolific Year · Productive
❓
The Questioner
💎
Century Club · Bronze
🚀
Conference Pioneer
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Artificial Intelligence
(7)
Machine Learning
(6)
Deep Learning
(5)
Bayesian & Probabilistic
(4)
Core Methods
(4)
Learning Paradigms · Artificial Intelligence
(4)
Architectures
(3)
Learning Paradigms · Machine Learning
(2)
Learning Types · Deep Learning
(2)
Learning Types · Machine Learning
(2)
Optimization & Theory
(2)
Data Science & Analytics
(1)
Interdisciplinary
(1)
Knowledge & Reasoning
(1)
Natural Language Processing
(1)
Keywords
few-shot learning
(4)
translation equivariance
(2)
neural process
(2)
convolutional neural network
(2)
variational inference
(1)
transfer learning
(1)
continual learning
(1)
batch active learning
(1)
uncertainty quantification
(1)
batch normalization
(1)
educational resources
(1)
permutation equivariance
(1)
compositional generalization
(1)
maximum likelihood
(1)
machine learning
(1)
probabilistic inference
(1)
high-dimensional regression
(1)
bayesian active learning
(1)
sparse approximation
(1)
bayesian inference
(1)
Papers
Predictive Complexity Priors
AISTATS 2021
Convolutional Conditional Neural Processes
ICLR 2020
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
NeurIPS 2020
Permutation Equivariant Models for Compositional Generalization in Language
ICLR 2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning
ICML 2020
Bayesian Batch Active Learning as Sparse Subset Approximation
NeurIPS 2019
Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects
EMNLP 2019
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes
NeurIPS 2019
Linking Educational Resources on Data Science
AAAI 2019
Meta-Learning Probabilistic Inference for Prediction
ICLR 2019
Modeling Concept Dependencies in a Scientific Corpus
ACL 2016