:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	King, Ryan, Krueger, Conrad, Veselka, Ethan, Yang, Tianbao, Mortazavi, Bobak J.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.03832
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Efficient Contrastive Unimodal Pretraining Method for EHR Time Series Data
by: King, Ryan, et al.
Published: (2024)

Memory-Efficient Continual Learning with CLIP Models
by: King, Ryan, et al.
Published: (2026)

ArterialNet: Reconstructing Arterial Blood Pressure Waveform with Wearable Pulsatile Signals, a Cohort-Aware Approach
by: Huang, Sicong, et al.
Published: (2024)

AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-rays
by: Yi, Chenlang, et al.
Published: (2025)

Modeling variable guide efficiency in pooled CRISPR screens with ContrastiveVI+
by: Weinberger, Ethan, et al.
Published: (2024)

FeDABoost: Fairness Aware Federated Learning with Adaptive Boosting
by: Arachchige, Tharuka Kasthuri, et al.
Published: (2025)

MIMIC-Sepsis: A Curated Benchmark for Modeling and Learning from Sepsis Trajectories in the ICU
by: Huang, Yong, et al.
Published: (2025)

Continual Knowledge Consolidation LORA for Domain Incremental Learning
by: Paeedeh, Naeem, et al.
Published: (2025)

We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2026)

Universal Domain Adaptation Benchmark for Time Series Data Representation
by: Mussard, Romain, et al.
Published: (2025)

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
by: Luthra, Achleshwar, et al.
Published: (2025)

Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis
by: Yanes-Pulido, Javier, et al.
Published: (2026)

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
by: Wang, Bokun, et al.
Published: (2024)

Deep Joint Distribution Optimal Transport for Universal Domain Adaptation on Time Series
by: Mussard, Romain, et al.
Published: (2025)

TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
by: Si, Haotian, et al.
Published: (2024)

Continuous Cardiac Arrest Prediction in ICU using PPG Foundation Model
by: Kataria, Saurabh, et al.
Published: (2025)

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation
by: Sun, Hankang, et al.
Published: (2025)

A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental Safety
by: Li, Gang, et al.
Published: (2024)

Hardness of Learning Neural Networks under the Manifold Hypothesis
by: Kiani, Bobak T., et al.
Published: (2024)

Multimodal Deep Learning for Early Prediction of Patient Deterioration in the ICU: Integrating Time-Series EHR Data with Clinical Notes
by: Sadanandan, Binesh
Published: (2026)

Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark
by: Fawaz, Hassan Ismail, et al.
Published: (2023)

A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
by: Wang, Bokun, et al.
Published: (2023)

Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection
by: Thorat, Shantanu, et al.
Published: (2024)

Evaluating Temporal Plasticity in Foundation Time Series Models for Incremental Fine-tuning
by: Liu, Jia, et al.
Published: (2025)

TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
by: Huang, Yu-Hao, et al.
Published: (2025)

Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-Series
by: Mehdizavareh, Hadi, et al.
Published: (2024)

Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks
by: Zhang, Qianru, et al.
Published: (2025)

Evaluation of Machine and Deep Learning Techniques for Cyclone Trajectory Regression and Status Classification by Time Series Data
by: Lo, Ethan Zachary, et al.
Published: (2025)

Explainable Spatio-Temporal GCNNs for Irregular Multivariate Time Series: Architecture and Application to ICU Patient Data
by: Escudero-Arnanz, Óscar, et al.
Published: (2024)

Deep Time Series Models: A Comprehensive Survey and Benchmark
by: Wang, Yuxuan, et al.
Published: (2024)

FTMixer: Frequency and Time Domain Representations Fusion for Time Series Modeling
by: Li, Zhengnan, et al.
Published: (2024)

ICU-TSB: A Benchmark for Temporal Patient Representation Learning for Unsupervised Stratification into Patient Cohorts
by: Proios, Dimitrios, et al.
Published: (2025)

DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
by: Guo, Siqi, et al.
Published: (2026)

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
by: Cai, Yifu, et al.
Published: (2025)

TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
by: Li, Zhe, et al.
Published: (2024)

Myna: Masking-Based Contrastive Learning of Musical Representations
by: Yonay, Ori, et al.
Published: (2025)

CP-Prompt: Composition-Based Cross-modal Prompting for Domain-Incremental Continual Learning
by: Feng, Yu, et al.
Published: (2024)

TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection
by: He, Hui, et al.
Published: (2026)

Remembering by Reconstructing: Domain Incremental Learning With Test-Time Training on Video Streams
by: Swinnen, Jonathan, et al.
Published: (2026)

SimCS: Simulation for Domain Incremental Online Continual Segmentation
by: Alfarra, Motasem, et al.
Published: (2022)