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Found 5 papers, 0 papers with code
NashFormer: Leveraging Local Nash Equilibria for Semantically Diverse Trajectory Prediction
Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents.
Accelerating Understanding of Scientific Experiments with End to End Symbolic Regression
We develop a deep neural network (MACSYMA) to address the symbolic regression problem as an end-to-end supervised learning problem.
A novel stellar spectrum denoising method based on deep Bayesian modeling
This work proposes a novel stellar spectrum denoising method based on deep Bayesian modeling.
Denoising
Imputation
Instrumentation and Methods for Astrophysics
Using Sensory Time-cue to enable Unsupervised Multimodal Meta-learning
As data from IoT (Internet of Things) sensors become ubiquitous, state-of-the-art machine learning algorithms face many challenges on directly using sensor data.
Photometric Redshift Estimation for Quasars by Integration of KNN and SVM
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts.
Instrumentation and Methods for Astrophysics
