Deep Learning
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
Unlike most reinforcement learning agents which require an unrealistic amount of environment interactions to learn a new behaviour, humans excel at learning quickly by merely observing and imitating others.
TabMT: Generating Tabular data with Masked Transformers
Autoregressive and Masked Transformers are incredibly effective as generative models and classifiers.
Active Observing in Continuous-time Control
The decision-maker's observing policy must be timely
Active Observing in Continuous-time Control
The decision-maker's observing policy must be timely
GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising Hyeonsu Kim Department of Chemistry KAIST Daejeon, South Korea Jeheon Woo
As quantum chemical properties have a dependence on their geometries, graph neural networks (GNNs) using 3D geometric information have achieved high prediction accuracy in many tasks.
GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising Hyeonsu Kim Department of Chemistry KAIST Daejeon, South Korea Jeheon Woo
As quantum chemical properties have a dependence on their geometries, graph neural networks (GNNs) using 3D geometric information have achieved high prediction accuracy in many tasks.