Jake Snell

Publications by Year

Research Areas

Domain Adaptation and Few-Shot Learning, Machine Learning and Data Classification, Neural Networks and Applications, Generative Adversarial Networks and Image Synthesis, COVID-19 diagnosis using AI

Most-Cited Works

• → Prototypical Networks for Few-shot Learning(2017)5,184 cited
• → Meta-Learning for Semi-Supervised Few-Shot Classification(2018)726 cited
• → Learning Latent Subspaces in Variational Autoencoders(2018)71 cited
• → Learning to generate images with perceptual similarity metrics(2017)51 cited
• Lorentzian Distance Learning for Hyperbolic Representations(2019)
• Dimensionality Reduction for Representing the Knowledge of Probabilistic Models(2018)
• → Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes(2020)8 cited