Technology
a32539cb16274581a17e679f6046f4bf-Paper-Conference.pdf
In this study, we introduce a novel model framework TransVIP that leverages diverse datasets in a cascade fashion yet facilitates end-to-end inference through joint probability.
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
We propose a versatile framework that combines DEQ with off-the-shelf machine learning models for predicting Hamiltonians.
Streaming PCA for Markovian Data
Since its inception in 1982, Oja's algorithm has become an established method for streaming principle component analysis (PCA).
Simple, Scalable and Effective Clustering via One-Dimensional Projections
In large-scale applications, datasets often contain billions of high-dimensional points. Grouping similar data points into clusters is crucial for understanding and organizing datasets.
Reward Imputation with Sketching for Contextual Batched Bandits
Contextual batched bandit (CBB) is a setting where a batch of rewards is observed from the environment at the end of each episode, but the rewards of the non-executed actions are unobserved, resulting in partial-information feedback.