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cs.LG2026
Refined Grid Sampling for Efficient Implicit Neural Representations of Large-Scale Scientific Data
Guang Zhao, Xihaier Luo, Sean McCue +5
Implicit neural representations (INRs) offer a powerful framework for modeling high-dimensional physical fields, but their training remains inefficient because evaluating dense coo…
cs.LG2026
Efficient Neural Field Learning via Adaptive Coverage and Focused Sampling
Guang Zhao, Xihaier Luo, Huan-Hsin Tseng +4
Implicit neural representations (INRs) provide a flexible framework for modeling high-dimensional continuous fields, but their training is often inefficient due to uniform subsampl…
cs.LG2026
LeJOT-AutoML: LLM-Driven Feature Engineering for Job Execution Time Prediction in Databricks Cost Optimization
Lizhi Ma, Yi-Xiang Hu, Yihui Ren +2
Databricks job orchestration systems (e.g., LeJOT) reduce cloud costs by selecting low-priced compute configurations while meeting latency and dependency constraints. Accurate exec…