Papers
4,122 papers found
Physics-Informed Deep Learning and Compressive Collocation for High-Dimensional Diffusion-Reaction Equations: Practical Existence Theory and Numerics
Simone Brugiapaglia, Nick Dexter, Samir Karam et al.
Physics-informed Kernel Learning
Nathan Doumèche, Francis Bach, Gérard Biau et al.
Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficient-KAN and WAV-KAN
Subhajit Patra, Sonali Panda, Bikram Keshari Parida et al.
Piecewise deterministic sampling with splitting schemes
Andrea Bertazzi, Paul Dobson, Pierre Monmarché
Posterior and Variational Inference for Deep Neural Networks with Heavy-Tailed Weights
Paul Egels, Ismaël Castillo
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers
Fan Yang, Hongyang R. Zhang, Sen Wu et al.
PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks
Xiyue Zhang, Benjie Wang, Marta Kwiatkowska et al.
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
Keru Wu, Yuansi Chen, Wooseok Ha et al.
Proper losses regret at least 1/2-order
Han Bao, Asuka Takatsu
Quantifying the Effectiveness of Linear Preconditioning in Markov Chain Monte Carlo
Max Hird, Samuel Livingstone
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
Brian Liu, Rahul Mazumder
Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees
Ziwen Wang, Yancheng Yuan, Jiaming Ma et al.
Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis
Hongru Yang, Yingbin Liang, Xiaojie Guo et al.
Random ReLU Neural Networks as Non-Gaussian Processes
Rahul Parhi, Pakshal Bohra, Ayoub El Biari et al.
Rank-one Convexification for Sparse Regression
Alper Atamturk, Andres Gomez
Recursive Causal Discovery
Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari et al.
Regularized Rényi Divergence Minimization through Bregman Proximal Gradient Algorithms
Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
Regularizing Hard Examples Improves Adversarial Robustness
Hyungyu Lee, Saehyung Lee, Ho Bae et al.
Reinforcement Learning for Infinite-Dimensional Systems
Wei Zhang, Jr-Shin Li
Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization
Sébastien J. Petit, Julien Bect, Emmanuel Vazquez
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection
Chengde Qian, Guanghui Wang, Changliang Zou
Reward-Directed Score-Based Diffusion Models via q-Learning
Xuefeng Gao, Jiale Zha, Xun Yu Zhou