Kevin Swersky

11

Papers

9,661

Total Citations

Papers (11)

Prototypical Networks for Few-shot Learning

NeurIPS 2017arXiv

Directly Fine-Tuning Diffusion Models on Differentiable Rewards

CUF: Continuous Upsampling Filters

Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions

Generative Moment Matching Networks

Scalable Bayesian Optimization Using Deep Neural Networks

Learning Memory Access Patterns

Flexibly Fair Representation Learning by Disentanglement

Graph Normalizing Flows

Neural Execution Engines: Learning to Execute Subroutines

Big Self-Supervised Models are Strong Semi-Supervised Learners