Good Papers

Showing papers from Ocean University of China Show all papers

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NeurIPS 2026YantaiSoochowOcean University of ChinaTime series forecasting

OTformer: Non-Stationarity-Aware Adaptive Optimal Transport Attention for Time Series Forecasting

Zhaowei Liu, Kaixiang Wang, Sheng Liu, zengyang zhang and 7 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026Ocean University of ChinaZhejiangNavigation & SLAM

DyPSI: Dynamic Physics Sensing via Joint Field and Sensor-Trajectory Generation

Yizhou Zhang, Panqi Chen, Lei Cheng, Ting Zhang and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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medium 0/10
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57%Worth a look
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NeurIPS 2026Dalian MaritimeGuangzhouOcean University of ChinaNortheasternPrivacy

LDPCache: Locally Differentially Private Multi-Query Processing with Cache Optimization for Large Language Models

Haoqiang Shi, Ning Wang, Chuan He, Qian Ma and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026Ocean University of ChinaSan Diego StateDiffusion models

EGCA: A Spectral Perspective on Forward Process Design in Diffusion Models

Chi Zhang, Guichao Chang, Sirui Liu, Xin Zhang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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medium 0/10
strict 0/5
78%Highly rated
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NeurIPS 2026JilinOcean University of ChinaPhysics-informed ML & PDEs

Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners

NPBS learns Born-series preconditioners in residual coordinates with metric-matched training, reducing Helmholtz iterations up to 1.9× versus direct residual learning and over 20× versus classical CBS.

Juntao Wang, Jiwei Jia, Xinliang Liu

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 2/5
medium 7/10
strict 2/5