2 citations · 7 across the 8 of their papers we have counts for
10 papers
SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference
Zahra Moslemi, Ziyi Liang, Babak Shahbaba
Bayesian predictive regions account for parameter uncertainty but can be poorly calibrated under model misspecification, even with expensive full MCMC. Cheaper approximations such…
ConformalHDC: Uncertainty-Aware Hyperdimensional Computing with Application to Neural Decoding
Ziyi Liang, Hamed Poursiami, Zhishun Yang +5
Hyperdimensional Computing (HDC) offers a computationally efficient paradigm for neuromorphic learning. Yet, it lacks rigorous uncertainty quantification, leading to open decision…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Heterogeneous Graph Alignment for Joint Reasoning and Interpretability
Zahra Moslemi, Ziyi Liang, Norbert Fortin +1
Multi-graph learning is crucial for extracting meaningful signals from collections of heterogeneous graphs. However, effectively integrating information across graphs with differin…
Conformal Inference for Open-Set and Imbalanced Classification
Tianmin Xie, Yanfei Zhou, Ziyi Liang +2
This paper presents a conformal prediction method for classification in highly imbalanced and open-set settings, where there are many possible classes and not all may be represente…
Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning
Ziyi Liang, Annie Qu, Babak Shahbaba
Developing effective multimodal data fusion strategies has become increasingly essential for improving the predictive power of statistical machine learning methods across a wide ra…
Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems
Ziyi Liang, Tianmin Xie, Xin Tong +1
We develop a conformal inference method to construct a joint confidence region for a given group of missing entries within a sparsely observed matrix, focusing primarily on entries…
Conformal inference is (almost) free for neural networks trained with early stopping
Ziyi Liang, Yanfei Zhou, Matteo Sesia
Early stopping based on hold-out data is a popular regularization technique designed to mitigate overfitting and increase the predictive accuracy of neural networks. Models trained…
Integrative conformal p-values for powerful out-of-distribution testing with labeled outliers
Ziyi Liang, Matteo Sesia, Wenguang Sun
This paper develops novel conformal methods to test whether a new observation was sampled from the same distribution as a reference set. Blending inductive and transductive conform…
A Locally Adaptive Algorithm for Multiple Testing with Network Structure
Ziyi Liang, T. Tony Cai, Wenguang Sun +1
Incorporating auxiliary information alongside primary data can significantly enhance the accuracy of simultaneous inference. However, existing multiple testing methods face challen…