Papers
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules
Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim et al.
pathGCN: Learning General Graph Spatial Operators from Paths
Moshe Eliasof, Eldad Haber, Eran Treister
Path-Gradient Estimators for Continuous Normalizing Flows
Lorenz Vaitl, Kim Andrea Nicoli, Shinichi Nakajima et al.
PDE-Based Optimal Strategy for Unconstrained Online Learning
Zhiyu Zhang, Ashok Cutkosky, Ioannis Paschalidis
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs
Zhengyang Shen, Tao Hong, Qi She et al.
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
Yang Zhao, Hao Zhang, Xiuyuan Hu
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
Mayee Chen, Daniel Y Fu, Avanika Narayan et al.
Permutation Search of Tensor Network Structures via Local Sampling
Chao Li, Junhua Zeng, Zerui Tao et al.
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
Alberto Bietti, Chen-Yu Wei, Miroslav Dudik et al.
Personalized Federated Learning through Local Memorization
Othmane Marfoq, Giovanni Neglia, Richard Vidal et al.
Personalized Federated Learning via Variational Bayesian Inference
Xu Zhang, Yinchuan Li, Wenpeng Li et al.
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning
Boxiang Lyu, Zhaoran Wang, Mladen Kolar et al.
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets
Han Zhong, Wei Xiong, Jiyuan Tan et al.
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Laixi Shi, Gen Li, Yuting Wei et al.
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning
Yunfei Li, Tian Gao, Jiaqi Yang et al.
PINs: Progressive Implicit Networks for Multi-Scale Neural Representations
Zoe Landgraf, Alexander Sorkine Hornung, Ricardo S Cabral
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
Ling Pan, Longbo Huang, Tengyu Ma et al.
Planning with Diffusion for Flexible Behavior Synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum et al.
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization
Minghuan Liu, Zhengbang Zhu, Yuzheng Zhuang et al.
PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information
Changbin Li, Suraj Kothawade, Feng Chen et al.
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
Qingru Zhang, Simiao Zuo, Chen Liang et al.
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
Amin Ghiasi, Hamid Kazemi, Steven Reich et al.
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correira et al.
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Pengyi Li, Hongyao Tang, Tianpei Yang et al.
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Xingang Peng, Shitong Luo, Jiaqi Guan et al.