Publications

* denotes equal contribution or advising; † denotes corresponding author

Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance Sampling
Xihaier Luo†, Samuel Lurvey, Yi Huang, Yihui Ren, Jin Huang, Byung-Jun Yoon
NeurIPS - Neural Compression Workshop 2024
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events
Ayush Khot, Xihaier Luo, Ai Kagawa
NeurIPS - Machine Learning and the Physical Sciences Workshop 2024
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
Xihaier Luo†, Xiaoning Qian, Byung-Jun Yoon
ICML 2024
Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction
Wei Xu, Derek Freeman DeSantis, Xihaier Luo, Avish Parmar, Klaus Tan, Balu Nadiga, Yihui Ren, Shinjae Yoo
AAAI - XAI4Sci workshop 2024
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
Xihaier Luo†, Wei Xu, Balu Nadiga, Yihui Ren, Shinjae Yoo
ICLR 2024
Biologically Interpretable VAE with Supervision for Transcriptomics Data Under Ordinal Perturbations
Seyednami Niyakan Xihaier Luo, Byung-Jun Yoon, Xiaoning Qian
ICLR 2024 Workshop on Machine Learning for Genomics Explorations
Reinstating Continuous Climate Patterns From Small and Discretized Data
Xihaier Luo†, Xiaoning Qian, Nathan Urban, Byung-Jun Yoon
ICML - SynS and ML Workshop 2023
Zero or Infinite Data? Knowledge Synchronized Machine Learning Emulation
Xihaier Luo†, Wei Xu, Yihui Ren, Shinjae Yoo, Balu Nadiga, Ahsan Kareem
NeurIPS - AI4Science Workshop 2022
Feature Importance in a Deep Learning Climate Emulator
Wei Xu, Xihaier Luo, Yihui Ren, Ji Hwan Park, Shinjae Yoo, Balu Nadiga
ICLR - AI: Modeling Oceans and Climate Change Workshop 2021