Search Results for author:
Found 6 papers, 3 papers with code
Deblurring 3D Gaussian Splatting
However, it suffers from severe degradation in the rendering quality if the training images are blurry.
Compact 3D Gaussian Representation for Radiance Field
On the other hand, 3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussisan-based representation and adopts the rasterization pipeline to render the images rather than volumetric rendering, achieving very fast rendering speed and promising image quality.
ChatPipe: Orchestrating Data Preparation Program by Optimizing Human-ChatGPT Interactions
Orchestrating a high-quality data preparation program is essential for successful machine learning (ML), but it is known to be time and effort consuming.
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning
We propose a Represent And Mimic (RAMi) framework for training 1) an identifiable latent representation to capture the independent factors of variation for the objects and 2) a mimic tree that extracts the causal impact of the latent features on DRL action values.
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
We describe NTS-NOTEARS, a score-based structure learning method for time-series data to learn dynamic Bayesian networks (DBNs) that captures nonlinear, lagged (inter-slice) and instantaneous (intra-slice) relations among variables.
Cracking the Black Box: Distilling Deep Sports Analytics
This paper addresses the trade-off between Accuracy and Transparency for deep learning applied to sports analytics.
