Search Results for author:
Found 7 papers, 5 papers with code
FACTS: A Factored State-Space Framework For World Modelling
World modelling is essential for understanding and predicting the dynamics of complex systems by learning both spatial and temporal dependencies.
Dual Advancement of Representation Learning and Clustering for Sparse and Noisy Images
Sparse and noisy images (SNIs), like those in spatial gene expression data, pose significant challenges for effective representation learning and clustering, which are essential for thorough data analysis and interpretation.
3D Feature Distillation with Object-Centric Priors
In this work, we show that this approach leads to sub-optimal 3D features, both in terms of grounding accuracy, as well as segmentation crispness.
Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter
To address these limitations, we develop a challenging benchmark based on cluttered indoor scenes from OCID dataset, for which we generate referring expressions and connect them with 4-DoF grasp poses.
NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes
We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues.
IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics
These obstacles prevent AI researchers from developing specialized methods for scientific designs.
Controllable Video Generation by Learning the Underlying Dynamical System with Neural ODE
Videos depict the change of complex dynamical systems over time in the form of discrete image sequences.
