Saved in:
| Main Authors: | Wan, Zhang, Wang, Shuo, Zhang, Xudong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.13060 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Prediction of Pass@k Scaling in Large Language Models
by: Kazdan, Joshua, et al.
Published: (2025)
by: Kazdan, Joshua, et al.
Published: (2025)
Optimization of geological carbon storage operations with multimodal latent dynamic model and deep reinforcement learning
by: Wang, Zhongzheng, et al.
Published: (2024)
by: Wang, Zhongzheng, et al.
Published: (2024)
Random-Set Graph Neural Networks
by: Woodley, Tommy, et al.
Published: (2026)
by: Woodley, Tommy, et al.
Published: (2026)
Can-SAVE: Deploying Low-Cost and Population-Scale Cancer Screening via Survival Analysis Variables and EHR
by: Philonenko, Petr, et al.
Published: (2023)
by: Philonenko, Petr, et al.
Published: (2023)
Curious Causality-Seeking Agents Learn Meta Causal World
by: Zhao, Zhiyu, et al.
Published: (2025)
by: Zhao, Zhiyu, et al.
Published: (2025)
Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon
by: Tavares, Ramon, et al.
Published: (2024)
by: Tavares, Ramon, et al.
Published: (2024)
On the Practice of Deep Hierarchical Ensemble Network for Ad Conversion Rate Prediction
by: Zhuang, Jinfeng, et al.
Published: (2025)
by: Zhuang, Jinfeng, et al.
Published: (2025)
Predictive Scale-Bridging Simulations through Active Learning
by: Karra, Satish, et al.
Published: (2022)
by: Karra, Satish, et al.
Published: (2022)
Cross-variable Linear Integrated ENhanced Transformer for Photovoltaic power forecasting
by: Gao, Jiaxin, et al.
Published: (2024)
by: Gao, Jiaxin, et al.
Published: (2024)
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
by: Zhang, Weijia, et al.
Published: (2024)
by: Zhang, Weijia, et al.
Published: (2024)
ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation
by: Mo, Junyi, et al.
Published: (2025)
by: Mo, Junyi, et al.
Published: (2025)
FreDF: Learning to Forecast in the Frequency Domain
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
Bayesian Networks and Machine Learning for COVID-19 Severity Explanation and Demographic Symptom Classification
by: Ajayi, Oluwaseun T., et al.
Published: (2024)
by: Ajayi, Oluwaseun T., et al.
Published: (2024)
Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems
by: Zhang, Hanyu, et al.
Published: (2024)
by: Zhang, Hanyu, et al.
Published: (2024)
Towards Reliable LLM Evaluation: Correcting the Winner's Curse in Adaptive Benchmarking
by: Xu, Yang, et al.
Published: (2026)
by: Xu, Yang, et al.
Published: (2026)
"Noisier" Noise Contrastive Eestimation is (Almost) Maximum Likelihood
by: Yu, Peiyu, et al.
Published: (2024)
by: Yu, Peiyu, et al.
Published: (2024)
Explainability of Complex AI Models with Correlation Impact Ratio
by: Sengupta, Poushali, et al.
Published: (2026)
by: Sengupta, Poushali, et al.
Published: (2026)
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations
by: Wang, Zhangyu, et al.
Published: (2024)
by: Wang, Zhangyu, et al.
Published: (2024)
A Statistical Theory of Regularization-Based Continual Learning
by: Zhao, Xuyang, et al.
Published: (2024)
by: Zhao, Xuyang, et al.
Published: (2024)
LLMs for Supply Chain Management
by: Wang, Haojie, et al.
Published: (2025)
by: Wang, Haojie, et al.
Published: (2025)
E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing
by: Sadhuka, Shuvom, et al.
Published: (2025)
by: Sadhuka, Shuvom, et al.
Published: (2025)
Building informative materials datasets beyond targeted objectives
by: Castañeda, Rafael Espinosa, et al.
Published: (2026)
by: Castañeda, Rafael Espinosa, et al.
Published: (2026)
Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models
by: Wang, Jiankun, et al.
Published: (2024)
by: Wang, Jiankun, et al.
Published: (2024)
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification
by: Nguyen, Hai-Vy, et al.
Published: (2024)
by: Nguyen, Hai-Vy, et al.
Published: (2024)
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
by: Zhang, Kexin, et al.
Published: (2023)
by: Zhang, Kexin, et al.
Published: (2023)
Machine Learning based Enterprise Financial Audit Framework and High Risk Identification
by: Yuan, Tingyu, et al.
Published: (2025)
by: Yuan, Tingyu, et al.
Published: (2025)
Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting
by: Ehsani, Sina, et al.
Published: (2024)
by: Ehsani, Sina, et al.
Published: (2024)
CVTN: Cross Variable and Temporal Integration for Time Series Forecasting
by: Zhou, Han, et al.
Published: (2024)
by: Zhou, Han, et al.
Published: (2024)
Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical Approach
by: Ferstad, Johannes O., et al.
Published: (2024)
by: Ferstad, Johannes O., et al.
Published: (2024)
A Metric-based Principal Curve Approach for Learning One-dimensional Manifold
by: Cuicizion, Eliuvish
Published: (2024)
by: Cuicizion, Eliuvish
Published: (2024)
I See, Therefore I Do: Estimating Causal Effects for Image Treatments
by: Thorat, Abhinav, et al.
Published: (2024)
by: Thorat, Abhinav, et al.
Published: (2024)
Auto-Regressive Moving Diffusion Models for Time Series Forecasting
by: Gao, Jiaxin, et al.
Published: (2024)
by: Gao, Jiaxin, et al.
Published: (2024)
Forecasting mortality associated emergency department crowding
by: Nevanlinna, Jalmari, et al.
Published: (2024)
by: Nevanlinna, Jalmari, et al.
Published: (2024)
Revisiting PCA for time series reduction in temporal dimension
by: Gao, Jiaxin, et al.
Published: (2024)
by: Gao, Jiaxin, et al.
Published: (2024)
Feature Group Tabular Transformer: A Novel Approach to Traffic Crash Modeling and Causality Analysis
by: Lares, Oscar, et al.
Published: (2024)
by: Lares, Oscar, et al.
Published: (2024)
Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series Measurements
by: Bouman, Roel, et al.
Published: (2024)
by: Bouman, Roel, et al.
Published: (2024)
Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
by: Vishwakarma, Harit, et al.
Published: (2024)
by: Vishwakarma, Harit, et al.
Published: (2024)
Binary Gaussian Copula Synthesis: A Novel Data Augmentation Technique to Advance ML-based Clinical Decision Support Systems for Early Prediction of Dialysis Among CKD Patients
by: Khosravi, Hamed, et al.
Published: (2024)
by: Khosravi, Hamed, et al.
Published: (2024)
Analyzing the Impact of Climate Change With Major Emphasis on Pollution: A Comparative Study of ML and Statistical Models in Time Series Data
by: Mishra, Anurag, et al.
Published: (2024)
by: Mishra, Anurag, et al.
Published: (2024)
Out-of-distribution Reject Option Method for Dataset Shift Problem in Early Disease Onset Prediction
by: Tosaki, Taisei, et al.
Published: (2024)
by: Tosaki, Taisei, et al.
Published: (2024)
Similar Items
-
Efficient Prediction of Pass@k Scaling in Large Language Models
by: Kazdan, Joshua, et al.
Published: (2025) -
Optimization of geological carbon storage operations with multimodal latent dynamic model and deep reinforcement learning
by: Wang, Zhongzheng, et al.
Published: (2024) -
Random-Set Graph Neural Networks
by: Woodley, Tommy, et al.
Published: (2026) -
Can-SAVE: Deploying Low-Cost and Population-Scale Cancer Screening via Survival Analysis Variables and EHR
by: Philonenko, Petr, et al.
Published: (2023) -
Curious Causality-Seeking Agents Learn Meta Causal World
by: Zhao, Zhiyu, et al.
Published: (2025)