ICML Papers 2020

Possible relevant papers from ICML 2020. We may want to make contact with authors about COVID-19 research.

Forecasting papers

Learning To Stop While Learning To Predict

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Predictive Sampling with Forecasting Autoregressive Models

Influenza Forecasting Framework based on Gaussian Processes

LEEP: A New Measure to Evaluate Transferability of Learned Representations

Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources

Few-shot Domain Adaptation by Causal Mechanism Transfer

Learning Optimal Tree Models under Beam Search

Learnable Group Transform For Time-Series

Problems with Shapley-value-based explanations as feature importance measures

The many Shapley values for model explanation

Cost-effective Interactive Attention Learning with Neural Attention Process

Adversarial Attacks on Probabilistic Autoregressive Forecasting Models