Papers
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
Lukas Gruber, Markus Holzleitner, Johannes Lehner et al.
Overcoming the Optimizer’s Curse: Obtaining Realistic Prescriptions from Neural Networks
Asterios Tsiourvas, Georgia Perakis
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
Michal Nauman, Michał Bortkiewicz, Piotr Miłoś et al.
OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
Bin Lu, Ze Zhao, Luyu Han et al.
PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models
Deividas Eringis, John Leth, Zheng-Hua Tan et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Jiyoung Whang
PAGER: Accurate Failure Characterization in Deep Regression Models
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi et al.
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh et al.
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao et al.
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Park, Hyowon Wi et al.
PAPM: A Physics-aware Proxy Model for Process Systems
Pengwei Liu, Zhongkai Hao, Xingyu Ren et al.
Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
Philip Schär, Michael Habeck, Daniel Rudolf
Parallelized Spatiotemporal Slot Binding for Videos
Gautam Singh, Yue Wang, Jiawei Yang et al.
Parameter-Efficient Fine-Tuning with Controls
Chi Zhang, Cheng Jingpu, Yanyu Xu et al.
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen et al.
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang et al.
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo, Trung Le, Long Tung Vuong et al.
Parameterized Physics-informed Neural Networks for Parameterized PDEs
Woojin Cho, Minju Jo, Haksoo Lim et al.
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
Phong C.H. Nguyen, Xinlun Cheng, Shahab Azarfar et al.
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition
Ziyang Zhang, Qizhen Zhang, Jakob Nicolaus Foerster
Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcalNP$-hard Problems
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.
Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling
Chengliang Liu, Gehui Xu, Jie Wen et al.
Partial Optimality in the Linear Ordering Problem
David Stein, Bjoern Andres