Search Results for author: Jiaming Cui

Found 5 papers, 3 papers with code

SAGE-ICP: Semantic Information-Assisted ICP

no code implementations11 Oct 2023 Jiaming Cui, Jiming Chen, Liang Li

Robust and accurate pose estimation in unknown environments is an essential part of robotic applications.

Pose Estimation

DF2: Distribution-Free Decision-Focused Learning

no code implementations11 Aug 2023 Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang

However, existing end-to-end DFL methods are hindered by three significant bottlenecks: model mismatch error, sample average approximation error, and gradient approximation error.

Autoregressive Diffusion Model for Graph Generation

1 code implementation17 Jul 2023 Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang

However, existing diffusion-based graph generative models are mostly one-shot generative models that apply Gaussian diffusion in the dequantized adjacency matrix space.

Denoising Graph Generation

End-to-End Stochastic Optimization with Energy-Based Model

1 code implementation25 Nov 2022 Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang

Decision-focused learning (DFL) was recently proposed for stochastic optimization problems that involve unknown parameters.

Scheduling Stochastic Optimization

EINNs: Epidemiologically-informed Neural Networks

1 code implementation21 Feb 2022 Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash

We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the theoretical grounds provided by mechanistic models as well as the data-driven expressibility afforded by AI models, and their capabilities to ingest heterogeneous information.

Inductive Bias

Cannot find the paper you are looking for? You can Submit a new open access paper.