Jangho Choi

Management Science and Operations Research · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jangho Choi trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Charles C. Holt (in Management Science and Operations Research)
  2. Slawek Smyl (in Management Science and Operations Research)

Papers from Jangho Choi's perspective

Ordered by how strongly the researchers Jangho Choi trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  2. Layer Normalization
  3. PyTorch: An Imperative Style, High-Performance Deep Learning Library
  4. Domain-Adversarial Training of Neural Networks
  5. Adversarial Discriminative Domain Adaptation
  6. Instance Normalization: The Missing Ingredient for Fast Stylization
  7. Domain Generalization via Invariant Feature Representation
  8. Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
  9. N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (International Conference on Learning Representations)
  10. Visual Domain Adaptation with Manifold Embedded Distribution Alignment (ACM Multimedia)

Their papers