Papers
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction
Dilip Arumugam, Satinder P. Singh
Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen et al.
PlasticityNet: Learning to Simulate Metal, Sand, and Snow for Optimization Time Integration
Xuan Li, Yadi Cao, Minchen Li et al.
Pluralistic Image Completion with Gaussian Mixture Models
Xiaobo Xia, Wenhao Yang, Jie Ren et al.
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Renrui Zhang, Ziyu Guo, Peng Gao et al.
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
Guocheng Qian, Yuchen Li, Houwen Peng et al.
PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points
Jing Tan, Xiaotong Zhao, Xintian Shi et al.
Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
Xiaoyang Wu, Yixing Lao, Li Jiang et al.
Poisson Flow Generative Models
Yilun Xu, Ziming Liu, Max Tegmark et al.
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds
Aoran Xiao, Jiaxing Huang, Dayan Guan et al.
Policy Gradient With Serial Markov Chain Reasoning
Edoardo Cetin, Oya Celiktutan
Policy Optimization for Markov Games: Unified Framework and Faster Convergence
Runyu Zhang, Qinghua Liu, Huan Wang et al.
Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems
Eric Yu, Zhizhen Qin, Min Kyung Lee et al.
Policy Optimization with Linear Temporal Logic Constraints
Cameron Voloshin, Hoang Le, Swarat Chaudhuri et al.
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks
Yen-Cheng Liu, CHIH-YAO MA, Junjiao Tian et al.
Polynomial Neural Fields for Subband Decomposition and Manipulation
Guandao Yang, Sagie Benaim, Varun Jampani et al.
Polynomial time guarantees for the Burer-Monteiro method
Diego Cifuentes, Ankur Moitra
Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games
Brian Zhang, Tuomas Sandholm
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits
Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
Positively Weighted Kernel Quadrature via Subsampling
Satoshi Hayakawa, Harald Oberhauser, Terry Lyons
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization
Jonathan Wilton, Abigail Koay, Ryan Ko et al.
Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers
Yuan Deng, Vahab Mirrokni, Hanrui Zhang
Posterior and Computational Uncertainty in Gaussian Processes
Jonathan Wenger, Geoff Pleiss, Marvin Pförtner et al.
Posterior Collapse of a Linear Latent Variable Model
Zihao Wang, Liu Ziyin
Posterior Matching for Arbitrary Conditioning
Ryan Strauss, Junier B Oliva