:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Datta, Saptati, Hengartner, Nicolas W., Pimonova, Yulia, Klein, Natalie E., Lubbers, Nicholas
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.18349
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Meta-Learning Linear Models for Molecular Property Prediction
by: Pimonova, Yulia, et al.
Published: (2025)

Differentially private Bayesian tests
by: Chakraborty, Abhisek, et al.
Published: (2024)

Bayes factor functions for testing partial correlation coefficients
by: Datta, Saptati
Published: (2025)

Learning with Sparsely Permuted Data: A Robust Bayesian Approach
by: Chakraborty, Abhisek, et al.
Published: (2024)

UnMarker: A Universal Attack on Defensive Image Watermarking
by: Kassis, Andre, et al.
Published: (2024)

Meta-learning to Address Data Shift in Time Series Classification
by: Myren, Samuel, et al.
Published: (2026)

Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials
by: Matin, Sakib, et al.
Published: (2025)

Optimal Invariant Bases for Atomistic Machine Learning
by: Allen, Alice E. A., et al.
Published: (2025)

Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
by: Srikishan, Bharat, et al.
Published: (2025)

DiffBreak: Is Diffusion-Based Purification Robust?
by: Kassis, Andre, et al.
Published: (2024)

Hybrid-Task Meta-Learning: A GNN Approach for Scalable and Transferable Bandwidth Allocation
by: Hao, Xin, et al.
Published: (2023)

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
by: Koermer, Scott, et al.
Published: (2025)

Riemannian Geometric-based Meta Learning
by: Park, JuneYoung, et al.
Published: (2025)

Fair Resource Allocation in Multi-Task Learning
by: Ban, Hao, et al.
Published: (2024)

Loss Landscape Geometry and the Learning of Symmetries: Or, What Influence Functions Reveal About Robust Generalization
by: Amarel, James, et al.
Published: (2026)

Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
by: Santos, Javier E., et al.
Published: (2025)

Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits
by: Duong, Thang, et al.
Published: (2025)

Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit
by: Zhang, Chaozhi, et al.
Published: (2024)

Meta-Learning with Heterogeneous Tasks
by: Si, Zhaofeng, et al.
Published: (2024)

The Geometric Structure of Models Learning Sparse Data
by: Walker, Thomas, et al.
Published: (2026)

DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks
by: Cui, Wei, et al.
Published: (2025)

Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials
by: Rodriguez, Austin, et al.
Published: (2026)

Task Addition in Multi-Task Learning by Geometrical Alignment
by: Yim, Soorin, et al.
Published: (2024)

Hacking Task Confounder in Meta-Learning
by: Wang, Jingyao, et al.
Published: (2023)

Practical Multi-Task Learning for Rare Conversions in Ad Tech
by: Dishi, Yuval, et al.
Published: (2025)

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
by: Corrado, Nicholas E., et al.
Published: (2026)

On the Meta-Design of Allocation Problems
by: Fischer-Abaigar, Unai, et al.
Published: (2026)

TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
by: Li, Hao, et al.
Published: (2025)

Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
by: Nguyen, Nicolas, et al.
Published: (2024)

Worst-Case Learning under a Multi-fidelity Model
by: Foucart, Simon, et al.
Published: (2024)

Learning Structured Compressed Sensing with Automatic Resource Allocation
by: Wang, Han, et al.
Published: (2024)

Set-based Meta-Interpolation for Few-Task Meta-Learning
by: Lee, Seanie, et al.
Published: (2022)

Bayes Factors Based on Test Statistics and Non-Local Moment Prior Densities
by: Datta, Saptati, et al.
Published: (2023)

Meta-Learned Basis Adaptation for Parametric Linear PDEs
by: Dwivedi, Vikas, et al.
Published: (2026)

Generalization vs. Memorization in Autoregressive Deep Learning: Or, Examining Temporal Decay of Gradient Coherence
by: Amarel, James, et al.
Published: (2025)

Multi-Task Combinatorial Bandits for Budget Allocation
by: Ge, Lin, et al.
Published: (2024)

Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models
by: Polle, Roseline, et al.
Published: (2025)

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
by: Byun, Ju-Seung, et al.
Published: (2024)

Hereditary Geometric Meta-RL: Nonlocal Generalization via Task Symmetries
by: Nitschke, Paul, et al.
Published: (2026)

Geometric Dynamics of Agentic Loops in Large Language Models
by: Tacheny, Nicolas
Published: (2025)